“Ladies and Gentlemen, Please Forgive Me Because…” I am a Catfish: Analysis of Gender Masking Techniques in The Circle

Karen Landeros, Gianelli Liguidliguid, Anna Kondratyeva, Jose Urrutia, Mariana Martin

On the Internet, no one knows you’re a dog…or a catfish. Or do they? On the reality TV show The Circle, contestants are not allowed to interact face to face—instead, they must communicate solely through a voice-activated “Circle Chat.” The anonymity of the show’s format allows contestants to “catfish” as individuals they perceive to be more attractive or likely to be popular, creating a fascinating environment to explore the perceived relationship between language and identity. This study will analyze the digital language devices, flirting habits, and text conversations sent by the contestants themselves to study if gendered language conventions exist and are followed in The Circle. Our research centers around Seaburn, a male contestant, who masks their gender identity by portraying the role of “Rebecca,” a shy, female contestant. We argue that Seaburn/Rebecca constructs their speech using stereotypically gendered language devices and concepts to effectively play the role of a woman. Our analysis highlights which features of online speech are considered to be feminine or masculine, with a specific focus on flirting, and gives insight on how prior knowledge of gendered language impacts how individuals mask their identity online.

Introduction

In our research, we were most interested in researching how contestants who catfish as another gender use linguistic features stereotypically associated with the opposite gender to mask their identity. Gender identity is often characterized by the linguistic patterns one makes use of, and a wide body of existing studies have explored the relationship between language and gender (Lakoff, 1973; Maharaj, 1995; Tannen, 2007). In an influential study, West and Zimmerman (1987) propose that gender is constructed through interactions and that individuals are continually involved in “doing gender.” A catfish would essentially take this idea of “doing gender” to the extreme, behaving and speaking entirely according to stereotypes about what a person of the opposite gender would do or say. The controlled, anonymous environment of The Circle creates a perfect setting to explore how online chat can be used to embody these gender stereotypes and expectations.

Men and women do not speak the same way online, although the ways in which they differ may contradict expectations. For instance, in an analysis of written speech on Facebook, women were “unsurprisingly” found to be warm and polite, but were also more assertive than men (Park et al., 2016). In another study, females were found to be more supportive, agreeable, and emotionally expressive than males in online discussion forums (Guiller & Durndell, 2007). With regards to specific devices used in online speech, females were more likely to use emojis and acronyms, while men were more likely to use hashtags in order to deliver information (Bamman et al., 2014; Ye et al., 2017).

Building off these existing patterns, we also examine the effect of flirting on online interactions. Studies have shown that there is indeed a difference in the flirting techniques used by men and women, which apply regardless of sexual orientation (Clark et al., 2021). For instance, men are more likely to initiate flirting than women (Whitty, 2004). By examining the characteristics of how catfish speak online, both while flirting and throughout the show, we explore how societal definitions of gender influence how individuals adopting false identities construct gender identity and roles within conversations.

Methods

Target Population

The target population of this study included the 14 contestants of The Circle. Our focus is on Seaburn, aka “Rebecca”, because he is the only catfisher in the season who is playing a different gender role. The other catfishers are simply masking as “hotter” versions of themselves.

Methodology

For our study, we utilized quantitative and qualitative data. The former was a preliminary data collection that involved collecting the frequency of emojis, hashtags, and acronyms used in any conversations with at least two interlocutors. This was done in order to see if any patterns of gendered language exist in The Circle. For qualitative data collection, we watched episodes of The Circle to seek out flirtatious conversations between any contestants and then chose a handful of text conversations to transcribe and further analyze. We then examined quantitative factors in flirting such as the gender of the initiator and proportion of sexual content.

Results/Analysis

Data Interpretation

We further stratified the data we collected from the linguistic device frequencies into two different charts. One type of chart highlights the number of occurrences per device between females and males. The other type of chart we created separates the proportioned data into three bars: catfisher, non-catfisher, and “Rebecca,” emphasizing the differences between Rebecca’s language as compared to both catfishers and non-catfishers in the show.

Emojis

In The Circle, emojis are used more often by males than females, as seen in Figure 1. This contradicts prior research on females being more likely to use emoticons than males (Parkins, 2012). Throughout the show, women tended to use emojis more often in same-gender conversations, while males used emojis more frequently in mixed-gender conversations for the purpose of being seen as more expressive by their female peers. The higher emoji usage by men may be a product of the prevalence of mixed and intimate conversations in The Circle, with men being more likely to use more “feminine” speech styles in these environments (Hilte et al., 2020).

Table 1: Percentage of the female and male contestants that use emojis

Noticeably, as seen in Table 2, Rebecca used emojis significantly less often than both the other catfishers and non-catfishers. This may have fueled other contestants’ suspicions about her “robotic” and overly formal speech.

Table 2: Proportioned average of emoji usage by non-catfishers, catfishers, and “Rebecca”

Hashtags

In online speech, hashtags are used for more than passing on information—they can also convey important emotions to others. In Table 3, we see that males on The Circle use hashtags more frequently than females. Since hashtags also serve as expressive forms (e.g. #YeahBuddy, #paesan), the data falls in line with previous literature that characterizes men’s speech to be more informative than females (Tannen, 2007).

Table 3: Percentage of the female and male contestants that use hashtagsphoto

As evidenced by Table 4, there was no significant difference between non-catfishers’ and catfishers’ hashtag usage. However, “Rebecca” used hashtags more than both their catfishing and non-catfishing peers. By using a significantly larger number of hashtags than the average contestant, “Rebecca” is still adhering to the “male” norm that men use substandard versions of language more than females (Holmes, 1992). Thus, as devices like hashtags are found to be more prevalent in male speech, Rebecca’s frequency of hashtag usage detracts from their success in masking their gender identity.

Table 4: Average occurrences of hashtag usage by non-catfishers, catfishers, and “Rebecca”

Acronyms

In The Circle, as shown in Table 5 acronyms are often used by females. This falls in line with previous literature, which suggests that acronyms can often serve as female markers in online communications (Bamman et al., 2014).

Table 5: Percentage of the female and male contestants that use acronyms

Since acronyms are an example of a nonstandard device of language, this analysis highlights how innovative female language can be in The Circle. Moreover, the data helped us further understand how the instances of acronyms usage may relate to how females typically act as facilitators in language (Tannen, 2007). For example, within the show there have been instances where the acronym “lol” has served as both a drive to alleviate tension as well as as a transitional phrase to facilitate a conversation by introducing a new topic.

In Table 6, we can see that “Rebecca” utilizes acronyms significantly more often than other contestants. This comparison led us to believe that “Rebecca” associated acronyms with female speech, and purposefully chose to use acronyms throughout their conversations in The Circle.

Table 6: Average occurrences of acronyms usage by non-catfishers, catfishers, and “Rebecca”

From the data shown above, we can see that gendered language in The Circle showed some deviations from stereotyped speech. We presume that “Rebecca” employed some markers of female speech based on preconceived notions of what females speak like online, but occasionally failed to adhere to the reality of female speech and mask their identity.

Flirting

The data on flirting (see Tables 7-10 under “Extended Tables”) showed that conversations by non-catfish were far more likely to be sexual in nature. One possible explanation for this is that the catfish did not feel as comfortable being sexual when portraying fake identities, though they did engage in flirting conversations to advance their status in the competition. With regards to flirting initiation, we saw that Rebecca initiated flirting much more often than a typical non-catfish woman, which falls in line with previous literature that shows that men are more likely to initiate flirting (Whitty, 2004). This suggests that “Rebecca” is still following some male flirting norms despite portraying a woman, potentially contributing to the other contestants’ suspicions about her.

Conversation Analysis

We analyzed three conversations in detail, but for this blog post we will be focusing on two. The first conversation that we analyzed occurred during Season 1 Episode 3, between Shubham (a non-catfisher) and “Rebecca” (a catfisher).

Example 1: a conversation between a non-catfisher and a catfisher flirting with linguistic devices

We found that “Rebecca” initiated the flirting first. In most instances (see Table 10), we found that men would first initiate flirting. However in this case, “Rebecca” flirted first in three of out of the four conversations they participated in (see Table 9). Another thing we noted was that “Rebecca” purposefully added the pet name hun at the end of her “Good morning” text. In the episode, Seaburn comments aloud that hun gives a more flirtatious aspect to the message. “Rebecca” also utilized the wink emoji (😉) at the end of this interaction to maintain this flirty atmosphere; this indicates that Seaburn made an effort to use more online emotionally-expressive language devices that are often associated with women (Parkins, 2012).

Below is our second example. Catfisher Alex is a heterosexual male catfishing as another heterosexual male named “Adam.” The second catfisher is the focus of our study, “Rebecca”.

Example 2. A conversation showing two catfishers flirting using varied speech styles

When looking at the structure of the conversation, there appears to be an imbalance of turn taking. In the first part of the conversation, “Rebecca” was successful in the use of OMG in the conversation, reflecting previous findings on females being more likely to use emojis (Whitty, 2004). At the end of the conversation, however, we see “Rebecca” use a pick up line which did not ultimately work in their favor, as “men are more likely than women to initiate flirting online” (Whitty, 2004). Due to this gender-masking flaw of initiating a pick up line in the conversation, catfisher Alex became suspicious of Rebecca’s true identity after the conversation. Overall, this conversation proved to be unsuccessful.

Discussion

Ultimately, “Rebecca” was not successful in their attempts to portray a woman through text-based online conversations. Rebecca did use some online language patterns associated with female speech, such as a high number of acronyms, but still spurred suspicions from 5 out of the 6 other remaining contestants by the end of the show. We believe that this could be partially attributed to the fact Rebecca used more hashtags and less emojis than the average female contestant, showing a discrepancy from typical female speech on the show. This discrepancy was also evidenced by her tendency to initiate flirting conversations, deviating from the behavior of other female contestants.

When explaining why they felt Rebecca was “fishy,” contestants named factors such as her over-the-top emotionality, her insincere “shy-girl” persona, and her strangely stilted, formal language (to which a lack of emojis likely contributed to). In addition to not adhering to the realistic patterns of female speech, Rebecca may have put misplaced emphasis on traits stereotypically associated with being feminine, such as shyness or emotionality, which was perceived as inauthentic by the other contestants.

Additionally, we saw no significant difference between the use of emojis, hashtags, and acronyms between catfish who were portraying the same gender and non catfish. This suggests that within the show, catfishers who portray same-gender identities of someone who is more attractive or desirable than themselves do not significantly shift their language in the process. “Rebecca’s” language patterns thus cannot be attributed to the mere fact of changing her identity, but to the fact that “Rebecca” portrayed a different gender in the process.

In our discussion of our results, we must also acknowledge some key limitations of our research. Because this is a reality TV show, the show’s content is highly edited (and possibly even scripted) by producers to create a coherent narrative or to feature the most exciting moments of the series. Furthermore, since the contestants were being constantly filmed, they were also likely to filter their speech. Because the contestants’ speech is filtered, edited, and constructed to fit the needs of reality TV, we do not know if the speech patterns we have access to truly reflect the way that they would speak online.

Another approach to our research relates to concepts shared by actor Joseph Gordon-Levitt in a TedTalk about how social media has ruined our creativity. Instead of striving to collaborate with others and learn from them, Gordon-Levitt says that we see everyone as competition and only want tangible proof of the attention we get (e.g., Instagram followers). Within The Circle, instead of saying that Rebecca adhered to inaccurate stereotypes of female speech, another approach could be to say that Rebecca simply lacked creativity in how to use language due to the competitive nature of the show and the need to get positive attention from others.

In terms of directions for future research, we think that a promising avenue could be exploring catfishers’ language use in text-based conversations. Because The Circle is voice-activated and auto-corrects the contestants’ speech and spelling, the show’s format does not allow for either ordinary spelling mistakes or purposeful alternative spelling (for example, writing “luv” instead of “love”). Exploring how gendered linguistic features are shown through text conversations can further address similar questions, such as which gender is more likely to engage in intentional misspellings, or how spelling errors impact flirting success.

 

Tables Extended

Table 7: Percentage of sexual vs. nonsexual content in flirting conversations with catfishers (including Rebecca)
Table 8: Percentage of sexual vs. nonsexual content in flirting conversations with non-catfishers
Table 9: Percentage of instances flirting was initiated by Rebecca
Table 10: Proportion of flirting conversations initiated by both non-catfish men and non-catfish women

 

References:

Bamman, D., Eisenstein, J., & Schnoebelen, T. (2014). Gender identity and lexical variation in social media. Journal of Sociolinguistics, 18(2), 135–160. https://doi.org/10.1111/josl.12080

Bryne, S., Harcourt, T., Lambert, S., Lilley, D., Price, S., Fenster, C., Foster, R., & Ireland, T. (Executive Producers). (2020). The Circle [TV Series]. Studio Lambert; Motion Content Group; Netflix.

Clark, J., Oswald, F., & Pedersen, C. L. (2021). Flirting with gender: The complexity of gender in flirting behavior. Sexuality & Culture. doi:10.1007/s12119-021-09843-8

Guiller, J., & Durndell, A. (2007). Students’ linguistic behaviour in online discussion groups: Does gender matter? Computers in Human Behavior, 23(5), 2240-2255. doi:10.1016/j.chb.2006.03.004

Hilte, L., Vandekerckhove, R., & Daelemans, W. (2020). Linguistic Accommodation in Teenagers’ Social Media Writing: Convergence Patterns in Mixed-gender Conversations. Journal of Quantitative Linguistics, 1–28. https://doi.org/10.1080/09296174.2020.1807853

Holmes, J. (1992). Women’s talk in public contexts. Discourse & Society, 3(2), 131-150. http://www.jstor.org/stable/42887783

Lakoff, R. (1973). Language and woman’s place. Language in Society, 2(1), 45–80. https://web.stanford.edu/class/linguist156/Lakoff_1973.pdf

Maharaj, Z. (1995). A Social Theory of Gender: Connell’s “Gender and Power”. Feminist Review, (49), 50-65. doi:10.2307/1395325

Park, G., Yaden, D. B., Schwartz, H. A., Kern, M. L., Eichstaedt, J. C., Kosinski, M.,  Seligman, M. E. (2016). Women are warmer but no less assertive than men: Gender and language on facebook. PLOS ONE, 11(5). doi:10.1371/journal.pone.0155885

Parkins, R. (2012). Gender and Emotional Expressiveness: An Analysis of Prosodic Features in Emotional Expression. Griffith Working Papers in Pragmatics and Intercultural Communication, 5(1), 46-54.

Tannen, D. (2007). You just don’t understand: Women and men in conversation. HarperCollins Publishers.

TED. (2019, September 12). How craving attention makes you less creative | Joseph Gordon-Levitt [Video]. YouTube. https://www.youtube.com/watch?v=3VTsIju1dLI

West, C., & Zimmerman, D. H. (1987). Doing gender. Gender and Society, 1(2), 125-151. doi:http://www.jstor.org/stable/189945

Whitty, M.T. (2004). Cyber-flirting: An examination of men’s and women’s flirting behaviour  both offline and on the Internet. Behaviour Change, 21(2), 115-126.

Ye, Z., Hashim, N. H., Baghirov, F., & Murphy, J. (2017). Gender Differences in Instagram Hashtag Use. Journal of Hospitality Marketing & Management, 27(4), 386–404. https://doi.org/10.1080/19368623.2018.1382415

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Fanquan language: How Chinese Fandom Culture Sweeps the Nation

Hanlin Meng, Ming Chen, Tianyuan Yan, Weilin Zeng

‘yyds, u1s1, dbq…’ These indecipherable words all come from a prominent and active group of young people in China, namely the fans who are promoting campaigns for their idols online and call themselves Fanquan, the fan circle. As exclusive as their language seems, it has actually gained popularity among the masses. Would they eventually make it into the mainstream culture as some people are concerned about? Or would they perish after a short time period as others predict? We aim to examine the correlation between the emotional polarities of popular words from Fanquan language and their popularities, in order to gain some insight on the future of this online language register. We predict that Fanquan lexicon with positive and commendatory attributes are more easily accepted and used by the public. We have also found some fascinating phenomena going on with this virtual register such as language policing, through which we can show that people’s attitudes towards the language are actually reflections of their attitudes towards the population of its users.

Introduction and background

According to Yunfei Tan, a Chinese fan culture researcher, “In China, communities known as “fan circle” (饭圈, fànquān), transliterated from the English word ‘fan,’ have become prominent on Weibo, WeChat, QQ, and other social media platforms in the last decade distinguishing themselves from individual fans (散粉, sǎnfěn) who support their idols independently.” (Tan, 2020) In the 2010s, with the popularity of the Internet and the maturity of social media platforms like Sina Weibo, the fans of actors and singers started converging and building their groups on social media platforms. According to China People Think bank, most of these groups are combined by online female fans under 18 years old. On the one hand, the generations born in the 21st century enjoy decent material conditions to support their entertainment. On the other hand, most of them have no siblings due to the Chinese one-child policy, so they lack companions in their growth. The Internet is the best access for the fans who live diversely, to connect with others. Data shows that the number of fans in first-tier cities and fourth-tier cities is 10% higher than those living in other cities. (Yin, 2019) A salient characteristic of Fanquan language is its unique word choice on Media. Most words are original in various ways, so they are hard to understand for the people out of the circle. The exclusion makes the group enjoy their uniqueness, but it is observed that some novel words would spread in their daily conversation with others. Previous studies suggest some features of Fanquan lexicon that facilitate the spreading. (Lu, 2020) First of all, they are reproducible, which allows outsiders to mimic the use of Fanquan words. Secondly, the meanings of these words can change over time or in different contexts.

For example, “宝藏男孩” is used by fans to describe a male idol who has a tainted background. However, it is widely used outside the circle to refer to one who is versatile and gifted. It is evident that the emotions related to Fanquan lexicon can change drastically in the process of spreading. Finally, the spreading is heavily affected by people’s choice of words. Widely used Fanquan lexicon varieties are often related to trending events or applicable in multiple scenarios.

Based on previous studies, we decided to investigate the relationship between the spreading of Fanquan lexicon varieties and the emotions evoked by them. Fanquan words can be categorized as positive words and negative words. Usually, positive words are used to praise their idols. For example, the word ‘juejuezi’ is a popular Fanquan word to express admiration and can always be seen in the comments of their idols’ weibo (a platform like Twitter). However, there are also negative words for attacking the users who have negative words about their idols. The phrase ‘penzi’ is used to humiliate others that criticize their idols. We hypothesized that positive Fanquan words are more widely spread and accepted due to the variability of their meanings and more applicable scenarios compared to negative words.

Methods

Our methods consist of two parts. The first step was conducting interviews with Fanquan language users around us regarding their personal observations. Based on their accounts, we could hypothesize about the mechanisms under their linguistic behaviors. It follows that the second step was to collect responses to a list of survey questions about people’s actual use of Fanquan words and their preferences for semantic positivity or negativity.

Results and analysis

We found three interviewees, using Fanquan language at different levels and their idols are successful in different fields. Zhang Shihang has been an idol of a Korean band since her junior high. Defining herself as a moderately active user, Zhang treated Fanquan language positively and explained that the spread of the language was a process of renewing cyber languages. She added, “Fanquan word is easier to type on the keyboard and cover some ‘dangerous’ words at the same time. For example, we never say ‘jizi’ because the word related to money would be censored. Instead, we call it ‘jz’ to avoid the trouble.” Zhang always unconsciously uses yyds (greatest of all time), juele (perfect), and plmm (beautiful girls), these positive Fanquan words when talking with friends. She was pleased to explain these words to her friends to spread fan culture. Wang Durian, a fan of a Chinese table tennis player, is a severe user. She only uses the word for fun without thinking of its value. She agreed that Fanquan words are easy to understand within the circle, but she has to explain the meaning to her friends who are distant from the culture. The word she likes to use is also “yyds”.

From another interviewee, we have received some quite different opinions. Han, a 24-year-old female who has studied applied linguistics and education, expressed her concerns with the negative impact Fanquan language may have on standard Mandarin. For example, according to her, yyds (English cool, awesome) can express a lot of emotions, so people would cease to specify the language use and a lot of emotion words could die out. She has provided us with new perspectives to work on in terms of different biases on Fanquan language.

Focusing on the application degree as well as the public acceptance towards fandom lexicon, we surveyed 105 young people about their use of Fanquan words and preference for positive/neutral/negative words.

Diagram#1 shows data that was generated from question number 2 “Which following words do you know the meaning of?” Among the total of 105 participants of question 2, 89 know the meaning of more than half of the options. This further proves that – fandom lexicon is nowadays quite of a phenomenal word choice category. According to the data generated from Q2, fandom lexicon with positive attributes was chosen as “know the meaning of it” 338 times, this result has proven that they are wider known by the outsiders.

Diagram 1

Diagram#2 shows data which were generated from question number 3 “Which of the following words have you used before?” None of the options were left unchosen thus further explains that fandom lexicon are being widely applied to common daily context by outsiders of fan group members. According to the numerical data generated from Q3, fandom lexicon varieties with positive attributes are more likely to be applied at daily practice in comparison to those with neutral or negative attributes.

Diagram 2

 

In summary, the survey shows that the fan dictionary is not only widely known and accepted by outsiders in the fan group, but also accepted by the public and used for various purposes. In addition, another important thing we realized from this survey is that fandom dictionaries with positive attributes are generally more likely to be applied outside of fandom activities.

Since it is not very straightforward to investigate a language in its entirety in such a short passage, we would like to reference a theoretical framework from an earlier study by Teahlyn Crow (2019) on K pop language in online fandoms. First of all, we have identified the fans that are currently inventing Fanquan language as a community of speech, but we must also realize that Fanquan words alone have a wider variety of audience. The speaker does not have to fully develop their competence in Fanquan language before they can use it quite freely. That being said, it seems that the indexicalities of Fanquan words are still very robust. If a person uses Fanquan words frequently, then they are automatically identified to be a regular Fanquan language user, and there exists a stereotype that only active fans in online forums are such users. For example, the fans of a particular idol must coin words for themselves and for their idol. Identities can become very refined through language use. One can determine from a post that the fan might be a fan who not only loves her idol, but also wishes her idol to express love for another idol. This is called a CP fan, an abbreviation from English word couple.

The construction of a fan identity works both ways. Some online communities have an implicit rule that, when it comes to idol-related contents, only those who use Fanquan language can be considered true fans. Therefore, fans can create bonds and their own identities by performing linguistic activities.

Moreover, what we have found from Fanquan language features is astonishingly similar to what Crow (2019) has found in online Korean K-pop fandom and what Gardiner (2019) has found in online Japanese pop culture fandom. The most notable shared feature is language mixing including loanwords and some code-switching. The aforementioned word, CP fan, is an abbreviation made by blending English and Chinese, and there are a number of new word-compounding rules that could demonstrate fandom’s innovative power with languages. It is also worth mentioning that while Gardiner (2019) found Japanese fandom words to be mainly nouns or noun phrases, we do not see such restrictions with Mandarin fandom words. Rather, the exclusivity of Fanquan words is its most debated characteristic. The more involved the person is in the fandom culture, the more they are willing to use the language outside of fandoms and even offline in daily life, but interviewees who are not so invested in fan campaigns have commented that they do not wish Fanquan language to spread further, because it has no intrinsic value (c.f. Han’s example). Finally, the interviewees all agree that negative Fanquan language is only used to attack malicious people online. Our survey has attested that positive words are more likely to be used in communication outside of fandoms, while the negative words are not uncommon inside fandoms. These words have gotten out their original registers and acquired mainstream acceptance.

Discussion and conclusions

Overall, we have verified our hypothesis through interview analyses as well as survey data. The knowledge of Fanquan language is not limited to fans, but the majority of young people might have contact with it through friends, suggesting that Fanquan language and the fandom culture at its background are actually very influential. Those Fanquan words that can be used more widely are mostly positive words, although some negative words have emerged as not uncommon. More data is required to verify if those negative words are being widely used outside of fandoms, which can pose substantial challenges to our theory.

Furthermore, during our investigation with specific Fanquan words, we found that interestingly, negative Fanquan words are considered to be even more vicious than swears in standard Chinese, despite the fact that the latter typically involves offense on family while the former only involves the idols. This has been used as evidence by critics against Fanquan language on its hostility or aggressiveness. We hypothesize that the emerging stereotype imposed on Fanquan language declares that it has a more aggressive nature than standard language because of its association with a higher percentage of aggressive usage or users. Such attitudes have been accurately reflected in current Chinese literature and argued with little evidence. For example, Lv (2020) claims that all language that does not conform to mainstream culture, or themes of the current political agenda, should be eliminated and ‘purified’. Such censoring targeting Fanquan language is a form of language policing, which we did not anticipate but came up as a highly relevant issue that deserves more sociolinguistic research.

 

References

Crow, T. F. (2019). K-Pop, Language, and Online Fandom: An Exploration of Korean Language Use and Performativity amongst International K-Pop Fans. Northern Arizona University.

Gardiner, R. E. A. (2019). ‘Weeaboo Japanese’: exploring English-Japanese language-mixing in online Japanese popular culture fandom: a thesis presented in partial fulfilment of the requirements for the degree of Master in Philosophy in Linguistics at Massey University, Albany, New Zealand (Doctoral dissertation, Massey University).

Lv, W. (2020). The Analysis of the Language of “Fanquan” under the Perspective of Sociolinguistics. Modern Linguistics, 08(02), 185–191. https://doi.org/10.12677/ml.2020.82026

Lu, Huiran. 以模因理论解读“饭圈”用语传播,Journal of News Research,May. 2020, https://www.cnki.com.cn/Article/CJFDTotal-XWDK202010132.htm

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Fellas, is it really gay to express affection for your homies?

Joseph Anderson, Jason Luna, Ethan Perkins, Helia Woo

An increasing and alarming number of cishet men performing purportedly homosexual behavior can be seen on social media. Current research suggests there is also a decrease in homophobia and homohysteria. Our study aims to explore how changes in support of homosexuality have also changed the language of homosocial relationships. In this context, homohysteria is defined as the heterosexual’s fear of being thought gay when performing gender atypical behaviors. Homophobia is defined as attitudes and behaviors that demonstrate intolerance of sexual acts, identities, morality, and the rights of homosexuals. To test our hypothesis that cisgender heterosexual (cishet) men will use language commonly indexed and correlated with the language of women and homosexual men when interacting in homosocial conversations with close friends, we analyzed 40 TikTok videos which featured cishet men in homosocial environments, and recorded five 30–40-minute conversations that took place either in person or online via Zoom and Discord. We found that cishet men, when in a comfortable setting with other cishet men, seem to use linguistic patterns that are typically indexed with cishet women and gay men. These results suggest that our hypothesis is true, despite our limited data.

Intro

Like many of our peers, our nights are filled with casually staring at the screen of our phones, scrolling for hours through an endless number of TikTok videos. Yet, after watching some cute puppy videos, hilarious scripted comedy, and some fantastic lip-syncs, we noticed a common theme of the videos in between: TikToks of two allegedly straight men, going in for a kiss, only for the camera to cut out right before their lips would touch. The most puzzling part: the #nohomo and #homiesexual tags underneath.

In recent years, contemporary pop culture seems to have an obsession with homosexuality — just without the part that requires anyone involved to actually identify as non-heterosexual. Like the TikToks mentioned above, various other social platforms, such as YouTube and Instagram, seem to be becoming home to male influencers engaging in “gay” behaviors with other men, despite neither party involved actually identifying as part of the LGBTQ+ community. From the iconic “Two bros sitting in a hot tub” Vine (Figure 1, re-uploaded to YouTube here), to recent online discourse about men keeping their socks on during sex acts with other men to keep it “no homo” (Figure 2), performative homosexuality seems to always be played for comedic effect. However, with the emergence of the phenomenon of men “playing gay” online in conjunction with the introduction of words like “homiesexual,” we were curious as to the ways in which language played a role in homosocial relationships, or the relationships between cisgender heterosexual males.

Figure 1. A famous Vine where the user zooms in on two men, distanced in a hot tub, while singing “Two bros sitting in a hot tub five feet apart ‘cuz they’re not gay.”

 

Figure 2. A TikTok creator lies in bed cuddling with three of his close male friends until they become uncomfortable when they notice they don’t have socks on. (@chrisp118 on TikTok)

Background

Current literature identifies three phenomena — homophobia, homohysteria, and queerbaiting — as core to the emergence of the identity of the homiesexual, which, according to the NYT involves “straight men who go beyond bromance and display nonsexual signs of physical affection.”

  1. Homophobia is an umbrella term for all attitudes and behaviors that demonstrate intolerance of sexual acts, identities, morality, and the rights of homosexuals (McCormack & Anderson, 2014).
  2. Homohysteria involves the heterosexual male fear of being thought gay when performing gender atypical behaviors (McCormack, 2011).
  3. Queerbaiting and gaybait are the deliberate insertion of homoerotic subtext in order to court a queer following without actualizing the subtext (Brennan, 2018).

Primarily, research on the subject centers on how increases in the acceptance of homosexuality and decreases in homophobia and homohysteria have led to new interpretations of what it means to be a cishet male (McCormack & Anderson, 2010; McCormack, 2011). However, this interpretation of the construction of the cishet male identity focuses on the concept of “bromance” and conversational dyads rather than group relationships among men and lacks discussion of specific linguistic properties (Robinson et al, 2018). Still though, other literature discusses the stereotype of male conversation being emotionally closed and unaffectionate (Sargent, 2013, Roberts et al, 2017).

Our research aims to fill the gap between the identification of these cultural phenomena and the analysis of specific linguistic forms and explore how changes in support of homosexuality have also changed homosocial relationships. There is a dearth of research on the speech of straight men because the speech of straight men is commonly perceived as the norm to be compared against when investigating minority speech. Cameron (2014) comments that this might be because the foundations of the monolith that is straight speech include a massive, diverse group of individuals, meaning that it would be hard to identify straight men as a singular community of practice. In fact, heterosexuality could be seen as an unmarked sexual identity because it is society’s default and no one has to “come out” as straight.

Additionally, in the same speech, Cameron states that this lack of research may be due to the fact that advocating for more research on heterosexuality could be seen as hostile to the larger purpose of the study of language as activism meant to advocate for minority communities.

However, to understand the gender performance and gender identities and what place that has in the social landscape, especially for minorities, it is essential that we study all groups, including heterosexual men, in order to ascertain whether something is actually specific or actual indexical of certain identities.

There has also been some study of the concept of “sounding gay” and the idea that non-heterosexual men, specifically homosexual men, often index the speech of heterosexual men in order to seem “straight passing” (Gaudio, 1994). Though, again, not much work has been done to understand how straight individuals might index non-straight language.

So, after recognizing the phenomenon of cishet men possibly becoming more comfortable with non-traditional performances of masculinity, sexuality, and gender, we wanted to uncover if these beliefs might also be influencing the language of cishet men.

Hypothesis

We hypothesize that cisgender, heterosexual (cishet) men will use language commonly indexed and correlated with the language of women and homosexual men when interacting in homosocial conversations with close friends.

This language may include:

  • compliments on attractiveness
  • calling one another pet names
  • raising pitch and using falsetto
  • hedging
  • pausing

Methods

In order to shed light on this phenomenon, our research entailed two components: (1) a content analysis from popular social media clips and (2) conversational analysis of interactions among friend groups involving at least two cishet men.

1. Content Analysis:

We analyzed 40 TikTok videos from compilation videos on YouTube with titles such as “straight guys being gay guys” or from the TikTok tags “#nohomo” or #homiesexual”. This analysis was performed to reveal preliminary insights into what behaviors we might be searching for during real-life conversations. Primarily, we analyzed conversation sequencing, diction, and body language.

2. Conversational Analysis:

Subsequently, we recorded five 30 – 40 minute conversations either online (through Discord or Zoom) or in-person in groups of 3 to 5 people including the recorder. Participants were told that at some point during the conversation, the researcher would begin recording. Sometimes the participants would be informed when the recording would start and other times they would not.

Results and Analysis

TikTok Data

Observations of the TikToks included the following:

  • escalation, competition, one-upping (e.g., “gay chicken”)
  • mirroring couple-like behavior (e.g., using pet names, intimate physical behavior, a man engaging in activities with another man that he’s only done with his girlfriend)
  • signals of discomfort after initiating gay behavior
  • comedic effect created through heteronormativity
  • comedic effect created through homohysteria
  • comments about each other’s bodies
  • dropping the gay act in the presence of a third party
  • use of a third party (girlfriend or other audience) to signal that gayness is not serious
  • hypersexualization of gayness (e.g., horniness or making sexual advances being the foremost marker of gayness)
  • making advances at the expense of the other man’s comfort
  • gayness being ingrained in heterosexual male friendships
  • use of the phrase “no homo” to ward off homosexuality

Findings from the TikToks can be grouped into three categories: homohysteria and heteronormativity, gender roles and misconceptions about homosexuality, and the spectrum, or lack thereof, of male intimacy.

Homohysteria and heteronormativity

Typically, comedy involves surprise—a subversion of expectations. TikTok creators relied on the concept of heteronormativity, the assumption that everyone is straight, as well as the normalization of homohysteria to create a comedic effect. Cishet men also played up homohysteria for humor by acting gay or hinting at one another’s gayness, while simultaneously expressing discomfort.

Heteronormativity also manifested itself more subtly in other ways: men filmed gay TikToks in front of their girlfriends, reinforcing the norm of heterosexual hegemony by using the idea of gay couples as a joke (Figure 3). When calling other men by pet names, men occasionally used names typically associated with women, such as “baby girl,” once again reinforcing the norm that a couple consists of one man and one woman (Figure 4).

Figure 3. Two boys flirt with each other right before one of their girlfriends catches them from the backseat. (@elijah.samaha on TikTok)

 

Figure 4. A friend of a TikTok creator calls him “baby girl,” then makes him laugh by giving his justifications for the pet name. The captions read, “But if it made you hornay it also worked” and “Uncontrollable laughter*”. (@jonnickerson on TikTok)

Gender roles and misconceptions of homosexuality

Other TikToks revealed the gender norms prevalent between male relationships, as well as a clear misinterpretation of homosexuality by cishet men. Cishet men, in acting gay, often joked that their girlfriends wouldn’t “find out” ignoring morality (of cheating on a signficant other) in favor of producing a humorous effect (Figure 3). They also hypersexualized gayness; many interactions involved words such as “horny,” “sexy,” and words relating to the sexual organs, and behaviors such as moaning or eating a sausage. This hypersexualization often blurred the line of comfort for those on the receiving end of a straight man’s gay advances—many men were confused and/or uncomfortable, as evidenced by their facial expressions or verbal reactions, even though they did not resist (Figure 5).

These behaviors signal misconceptions, often harmful, about male homosexuality—that homosexuality is inherently more sexual or less ethical than heterosexuality. However, because of the comedic nature of such behaviors, it is also implied that many of these men are aware of their misconceptions and deliberately play on them to heighten the humorous effect. They also signal an adherence to gender norms, as we will discuss further in the conclusion.

Figure 5. A TikTok creator making unexpected advances towards a friend, resulting in initial surprise or disapproval. (@grahamnation_ on TikTok)

Extremes on the spectrum of male intimacy

Cishet men showed a tendency to either avoid any intimacy, or show it at an extreme level. In particular, men frequently said “no homo” to immediately eliminate any assumptions of legitimate homosexuality. On the other end of the spectrum, they often played “gay chicken” (in which they continued to act more and more gay until one person finally cracked) or tried to one-up each other in acts of gayness. In some situations, men did not necessarily try to compete with the other, but refused to show weakness by stepping away from their advances (Figure 6). These competition-centered interactions are likely attempts in asserting dominance and subordinating one another.

Figure 6. One man comes closer and closer to another, who stands still but suppresses his laughter. (@alexwillis1 on TikTok)

 

Discord Calls / In-Person Recordings Data

For the online Discord recordings, as well as the in-person recording, interactions were able to be placed in a few categories. Each interaction is numbered based on the order in which we are presenting them, rather than the order in which they were recorded. Firstly, many interactions could be considered compliments, both innocent (not inherently sexual) and explicit (sexual in nature). Figures 7.1 and 7.2 below show examples of innocent compliments, in which participants A and C compliment each other’s hair.

Conversation Analysis Transcription Key

Innocent Compliments

Figure 7.1. Transcript of first compliment about hair.
Figure 7.2. Transcript of second compliment about hair.

Physical Touching

In Figure 8.1 below, we can see another example of a compliment; however, A’s compliment of B’s physical appearance also includes physical touching. Here, as is shown in the ((double parentheses)), A touches B’s abdomen and chest while complimenting him. There were other instances of physical touching, such as the interaction in Figure 8.2, in which A slapped B’s buttocks.

Figure 8.1. Transcript of compliment about body, and physical touching.
Figure 8.2. Transcript of intimate physical touching.

Explicit Compliments

Other compliments given from one participant to another were explicitly sexual, such as the below interaction in Figure 9.

Figure 9. Transcript of a sexually-charged compliment.

In Figure 9, A and C were referring to participant B’s male character from the video game Destiny 2, with A referencing a specific meme in the last line.

Pet Names

A pet name was only recorded in one interaction, seen below in Figure 10, in which A referred to B as his “lil piss baby.”

Figure 10. Transcript of a pet name.

Other Flirtatious Interactions

Additional flirtatious behavior was recorded, including the interaction in Figure 11. For some context, A and B were comparing video game characters from Destiny 2, when C offered to show his character, jokingly, since he did not play the game.

Figure 11. Transcript of a flirtatious interaction.

Intonation

When it came to intonation changes (as illustrated in the figures by the up or down arrows), the pitch of the participants’ voices seemed to raise when mentioning a body part in a sexual manner. This is seen in Figure 9, when C mentioned “bulge,” as well as in Figure 11, when A mentioned “my ass.” Additionally, intonation rose when A and C were complementing each other in Figures 7.1 and 7.2. A’s intonation also significantly rose when calling B by a pet name, as shown in Figure 10.

Hedging

Finally, we looked at hedging, or filler words that mitigate or downplay the severity or seriousness of a statement. The most common hedges found in our data were “you know,” “I mean,” and “I don’t know, but.” An example of the hedge “you know” can be seen in Figure 8.1, after A complimented C. Additional hedges included “might” and “really,” as shown below in Figure 12, where A hedged his opinion on the TV show “The Office.”

Figure 12. Transcript of an instance of hedging.

 

Discussions and Conclusions

Our data and analysis support our hypothesis. Cisgender and heterosexual men, in interactions with other cisgender and heterosexual men, tend to use linguistic patterns indexed with gay men or straight women; these patterns include higher intonation and hedging. In addition, cishet men use flirtatious speech in these homosocial environments, such as compliments, pet names, and sexually-charged comments, many of which were observed with higher intonation. An important note to make, however, is that despite similarities in speech patterns, many of the behaviors cishet men exhibit in homosocial settings are not indexed with gay men or straight women. For instance, the hypersexualized actions cishet men engage with seem to be exclusive to cishet men.

The main conclusion we can draw from our findings is that despite decreasing levels of homophobia and shifting views on non-traditional forms of masculinity, sexuality, and gender, heteronormativity and gender norms remain prevalent. As explained in the analysis section, cishet men’s “gay act” relies on heteronormativity to create humor in the first place. Gender norms can explain the ubiquity of confusing or unwanted advances towards other men: it is likely that men expect other men to show less “fragility” and therefore “take it like a man,” as the saying goes. The convention of male dominance also may explain the competitive aspect of acting gay. Furthermore, the dissonance between the two extremes of male interaction (overly intimate or not intimate at all) implies once more the pervasiveness of gender roles and stereotypes, as men are expected to be less affectionate and more emotionally closed-off. Thus, although cishet men know how to index gay or non-cishet male identities, as indicated by their shifted speech patterns, they are still heavily influenced by larger outside forces that suggest our views have yet to fully break away from the heterosexual and patriarchal norms.

Additional Reading / Viewing

Everyone Is Gay on TikTok (New York Times)

The Evolution Of Queerbaiting: From Queercoding to Queercatching (YouTube – Rowan Ellis)

Project Presentation (Anderson, Luna, Perkins, Woo)

 

References

Brennan, Joseph. “Introduction: Queerbaiting.” The Journal of Fandom Studies 6.2 (2018): 105-113.

Cameron, D. (2014). Straight talking: the sociolinguistics of heterosexuality. Langage et société, (2), 75-93.

Gaudio, R. P. (1994). Sounding gay: Pitch properties in the speech of gay and straight men. American speech, 69(1), 30-57.

McCormack, M. (2011) Mapping the Terrain of Homosexually-Themed Language, Journal of Homosexuality, 58:5, 664-679, DOI: 10.1080/00918369.2011.563665

McCormack, M. (2011). The declining significance of homohysteria for male students in three sixth forms in the south of England. British Educational Research Journal, 37(2), 337-353.

McCormack, M., & Anderson, E. (2014). The influence of declining homophobia on men’s gender in the United States: An argument for the study of homohysteria. Sex Roles, 71(3), 109-120.

McCormack, M., & Anderson, E. (2010) The re-production of homosexually-themed discourse in educationally-based organised sport, Culture, Health & Sexuality, 12:8, 913-927, DOI: 10.1080/13691058.2010.511271

Roberts, S., Anderson, E., & Magrath, R. (2017), Continuity, change and complexity inthe performance of masculinity among elite young footballers in England. The British Journal of Sociology, 68: 336-357. https://doi.org/10.1111/1468-4446.12237

Robinson, S., Anderson, E., & White, A. (2018). The bromance: Undergraduate male friendships and the expansion of contemporary homosocial boundaries. Sex Roles, 78(1), 94-106.

Sargent, D. (2013). American masculinity and homosocial behavior in the bromance era.

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Love at First Site? The Impact of Medium and Sex on Flirting Behavior

Christian Bury, Maddy, Valerie Beketava, Marissa Schulner, Luming Zhou

Smiling at the cute cashier, batting your eyes at your work-crush, or even strutting up to greet an attractive stranger at the bar, whether Dr. Love himself, or merely an average joe looking to land a date, we’re all aware of the tried-and-true signs of flirting. It’s with this familiarity in mind, that the recent emergence of social media and popular dating apps have revolutionized these age-old flirting techniques, reimagining themselves in the form of risqué DM’s and overly animated texts featuring the all too infamous winky face emoji. Biological sex has long stood as the primary element of influence within flirting behavior, but with the prevalence of today’s digital technology, the actual medium of such communication has been introduced as yet another important factor regarding one’s approach to flirting. Despite this being the case, a few features of flirting remain ubiquitous across both face-to-face and virtual mediums regardless of biological sex: the use of compliments and exaggerated reactions. With this in mind, the following article lays-out and reflects on the aforementioned features of flirting, shedding light on how differences among sex and medium impact flirting behavior, perception, and tendencies.

Introduction

Before diving into all the nitty-gritty details of these recent observations, it is important that we introduce the background of such research, and more specifically, the features of flirting we will be paying special attention to. With longstanding studies on flirting and communication, it doesn’t take an astrophysicist to know that flirting relies heavily on non-verbal signals and exaggerated reactions such as laughing, smiling, looking someone in the eye for a significant period, and winking (Eckert & McConnell, 2003). For this exact reason, more contemporary research has concluded that without the traditional non-verbal signals of face-to-face communication, virtual flirting tends to rely on emojis, capitalization, and punctuation, as substitutes for conveying exaggerated excitement (Whitty, 2004). Our study of “exaggerated reactions” refers to the act of responding over-enthusiastically while flirting, usually laughing, smiling, or speaking louder and faster to signal interest and excitement. More specifically, this feature may take form in face-to-face contexts by giggling at an attractive person’s joke as if it’s way funnier than it actually is, or appear in a virtual sense, with the excessive use of emojis, punctuation, and capitalization, while texting “HAHAHA…waaaaiitt, I LOOOOVE that!!!!” Likewise, in regard to modern analysis surrounding the use of compliments between men and women, it’s been widely observed that women are more likely to both give out and accept compliments, while men are more likely to deflect and misread compliments when flirting (Tannen, 1990). From this standpoint, we’ve chosen to further examine such behavior, particularly researching what we’ve classified as “direct and risque compliments.” This feature refers to the act of essentially cutting straight to the point and making a flirtatious or sexually suggestive compliment while flirting. Most notably, such behavior may be observed within the likes of face-to-face flirting by telling someone “you’re gorgeous,” or appear in a virtual context while sliding into someone’s DM’s to say “you’re super hot, can I get your snap?” Now at this point, you may be thinking so what’s the big deal? Well, by taking these features into account, we’ve developed exciting new insight on the medium and types of compliments preferred by men and women, in addition to which medium is perceived to involve more exaggerated reactions, as well as direct and risqué compliments. We predict that flirting face-to-face is the preferred medium of both men and women, being perceived as more sincere, and therefore, more effective. Moreover, we also expect to find that flirting virtually tends to involve more direct and risqué compliments, as well as exaggerated reactions.

Methods

With regards to the methodology of such research, we decided to approach this study with three separate phases and means of collecting data. First and foremost, we developed a multiple choice google survey, gathering responses from 27 male and 27 female UCLA students. In particular, this survey gauged the tendencies and perceptions, as well as the use of compliments and exaggerated responses by men and women when flirting face-to-face and/or virtually. Next, we cross compared our survey results with 14 anonymously submitted screenshots of flirting over Tinder, Instagram DM’s, and Text messages, effectively countering the potential survey bias of our data by presenting more “real-world” flirting behavior in practice. Lastly, we gathered and analyzed an assortment of media clips containing flirting scenes from various movies and shows, once again cross referencing such examples with our survey data and screenshots of virtual flirting to develop more comprehensive results. 

Results and Analysis

Moving on to the results and analysis of this three-phase approach to data collection, we see that our survey results indicate that men and women are strikingly similar when it comes to their perception and use of really any notable feature and medium of flirting. In this case, our survey data shows that the only notable disparity between sex appears over which medium is more likely to contain exaggerated reactions, with men saying that virtual flirting contains more exaggerated reactions, while women reported the contrary, highlighting the exaggerated reactions of face-to-face flirting instead (as seen in Graph #5). Beyond this minor disagreement, both men and women said that face-to-face was their preferred flirting medium (Graph #1), agreeing that it’s more sincere (Graph #2), and therefore, more effective (Graph #3), while also perceiving that virtual flirting tends to involve far more direct and risqué compliments (Graph #4).

 

 

 

 

 

 

 

 

 

 

 

Taking this into account, our analysis of the virtual flirting screenshots showed that in many cases people will say things online that they may not say in person (Screenshot #1 and #2). This observation carries over similarly to an apparently high volume of exaggerated messages and responses (Screenshot #2 and #3). As noted earlier, this behavior likely stands as a means of compensating for the lack of traditional nonverbal flirting signals missing from virtual mediums. Lastly, our examination of media clips focused mainly on scenes from the films “Back to the Future”, “Crazy, Stupid, Love”, and “The Departed” (see links below).

“Back to the Future” Flirting Scene

“Crazy, Stupid, Love” Flirting Scene

“The Departed” Flirting Scene

In each case, all three clips displayed an exchange of compliments, usually coming from the man initially, as well as indications of exaggerated reactions, usually occurring in the form of giddy laughter, smiling, and louder, faster speech.

Discussion and Conclusions

Relying on surveys, research, and media analysis we draw several conclusions regarding flirting behaviors among young adults. By analyzing our survey results we can conclude that flirting face-to-face is the preferred medium of both men and women. This came as no surprise to us but was very interesting to analyze the many possible reasons and explanations that resulted in this conclusion. One reason for this result is that both genders indicated that they found flirting in person to be perceived as more sincere, effective, and the most time effective method of getting to know a person they are attracted to. Virtual flirting was shown to be more prone to direct and risqué communication that can often be misinterpreted whereas in-person can be seen to show much more clear and precise expression of intentions. The more playful and sincere compliments observed through in-person flirting is preferred for both men and women over the more scandalous and risqué ones prevalent among virtual flirting. As we previously assumed, virtual flirting prompts much more exaggerated and animated reactions than in-person. We assume that this exaggerated behavior is used as an attempt to combat the non-verbal cues we get when flirting in person. These non-verbal cues include smiling, touching, laughing, as well as other micro-expressions we observe when you are attracted to another person. Those who are more introverted and less confrontational may prefer online flirting as their preferred medium as there is much less physical embarrassment when a flirting tactic fails to elicit the desired response. For an online flirting medium such as Tinder, where you most likely have not met the person, you are talking to and, the person may believe they have to come off strong to provoke a response and make an impression among a much larger pool of potential partners. While our survey did compare results among both men and women, our analysis found that the medium, rather than sex, has a much larger impact on the use and perception of compliments and exaggerated response when flirting. Overall, most of our research data and analysis confirmed our hypothesis that young adults prefer face-to-face over online flirting, leaving the door open for further insight that could promote future research on this topic.

 

 

References

Tannen, D. (1990). You just don’t understand: Women and men in conversation. New York, NY: Morrow.

Eckert, P., & McConnell-Ginet, S. (2003). Language and gender. Cambridge: Cambridge University Press.

Holmes, J. (1988). Paying compliments: A sex-preferential politeness strategy. Journal of Pragmatics, 12(4), 445–465. https://doi.org/10.1016/0378-2166(88)90005-7

Smith, J. (2014). The Perceived Impact of Online Versus Offline Flirting on Romantic Relationships . (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

Narissra M. Punyanunt-Carter and Thomas R. Wagner.Cyberpsychology, Behavior, and Social Networking.Apr 2018.229-233.http://doi.org/10.1089/cyber.2017.0608

Whitty, M.T. (2004). Cyber-flirting: An examination of men’s and women’s flirting behaviour  both offline and on the Internet. Behaviour Change, 21(2), 115-126

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“Do You Even Lift, Bruh… or Sis?” 💪: A Look into the Online Gendered Communication of Fitness Influencers on YouTube”

Hyung Joon (Joe) Kim, Jenny Elliott, Madeleine Song, Sophia King, Alison Tcheguini

With the rise of social media influencers, online public figures have become more attentive to how they communicate with their followers. In our research study, we assess the features of online gendered communication in comparison to the in-person gendered communication theories.

To do this, we chose YouTube fitness influencers as our main scope of study because “fitness” is a relatively gender-neutral category. By analyzing the influencers’ online comments, we discovered notable differences between male and female influencers’ responses to their fans. We found that women use certain linguistic features more frequently and that they used them in greater varieties. We believed this to be an indication of an emotional and expressive way of communicating. On the other hand, men generally used these linguistic tools less frequently and in less variety.

Overall, both males and females used supportive and rapport language. This is indicative of the fact that both seek to establish solidarity with their respective fan base. However, we found that men and women use these linguistic features to different extents, and differing the types of linguistic tools they use. In this regard, we observed a dichotomy of “calm vs emotional” which is a modern adaptation of the well-established “report vs rapport” model.

Introduction

Regardless of their content, social media influencers aim to grow and maintain an audience to ensure their platforms are marketable and profitable. We found there are several linguistic techniques these influencers adopt to build connections with their fans. In particular, they replied to their followers’ comments under their videos to facilitate connection with their audience, and, when doing so, utilized rapport-building linguistic features.

In general, men and women have been understood to communicate differently in the process of forming connections. We wanted to further investigate differences across genders in connection-building communication in the context of online social platforms.

These concepts guided our research, as we examine the linguistic differences of male and female influencers in their written responses to followers’ comments online. 

Background

Due to our scope of interest in influencers’ platform maintenance, we examined existing literature on gendered and computer-mediated communication.

The dominance model suggests that female language use reflects male dominance in society (Lakoff, 1975), whereas the difference model proposes that differences in language between men and women reflect different cultures of conversation (Tannen, 1990). Despite both styles serving the same communicative function, women use rapport-oriented conversation, which is more emotional, while men use report-talk, reporting fact-based information and competing for hierarchy in conversation (Tannen, 1990). Further work has been done on gendered communication differences to see what linguistic features can be attributed to men: in homosocial contexts, men use expressions like “dude” or “bro,” as their way of performing male expectations, indexing their heterosexuality to promote heterosexuality as their preferred orientation. (Van Herk, 2018, p.109).

Since we are looking at social media influencers, we also looked at computer-mediated communication (CMC) studies to see how these patterns reflect in a modern online context. The content of CMC messages by females is more expressive than males, reflecting a female’s social role of being emotionally expressive and collaborative, as mentioned in the Tannen’s model (Fox et. al., 2007, p. 395). Regarding CMC-specific linguistic features like emoticons, studies suggest that females use emoticons as a means of expressing solidarity, support, positive feelings, and gratitude––reinforcing the existing stereotype that females are more emotional than males (Wolf, 200, p. 827). Literature on text-based punctuation in online messages suggests that digital cues, such as excessive punctuation and capitalization, increased the bonding of female friendships (Sherman et. al., 2013). These cues were made frequently by young women to convey emotion in their text-based conversations.

Our main research question is the following: “To what extent does the gender identity of YouTube fitness influencers affect the digital linguistic expressions they use to establish solidarity with their followers?”

In our research, we observed that females used more frequent expressions than males across four different features we examined; however, by narrowing down on more specific sub-categories under the features, we found that even though males and females used different linguistic expressions, both male and female fitness influencers were using different tools to pursue the same purpose of establishing solidarity with their fans.

Methods

We conducted our study by analyzing the computer-mediated communication used by ten female and ten male YouTubers. We narrowed our sample choice by selecting YouTubers who belong to the fitness industry, create fitness content for YouTube, and speak English. Our sample was categorized into two sections: influencers with less than one million subscribers (Table 1) and influencers with over one million subscribers (Table 2). To avoid bias, data were collected from each influencer by randomly selecting ten interaction-based comments from two randomly selected workout videos.

We categorized our data into four linguistic features based on the most salient differences we observed among the comments of male and female fitness influencers. Our data was analyzed based on the frequency of emojis, exclamation points, capitalization, and pet names. In terms of emojis, we looked at the types of emojis that were being used differently by males and females. The specific emojis were grouped into three distinct categories: facial expressions, gestures, and non-human symbols (fire, stars, sweat, etc).

Table 1. Fitness influencers with less than 1M Followers

Results and Analysis

First, we looked at the use of emojis in YouTube comments from female and male influencers. Symbol and facial expression emojis were popular for women, using a variety of faces such as 🤪 and hearts 💖.

Figure 1: Emoji Usage: Make vs Female Influencers

Men also used emojis frequently but the specific emojis they used differed from what females used––males instead opted for symbols like 🔥 or 💦. 

Overall, women used more expressive facial emojis along with many gesture emojis (Figure 1). In general, women used facial expression, symbol and gesture emojis more frequently than men.

Second, we analyzed punctuation by examining the use of exclamation points in influencers’ responses to comments. Women tended to use exclamation points in most of their replies, often using several exclamation points in a row. In contrast, males did not use exclamation points as frequently, and when they did, they only used 1-2 per comment.

Figure 2: Exclamation Usage: Male vs Female Influencers

While men did use exclamation points, they did not use them to the same extent as women. Women used exclamation points more frequently, totaling over 100 times throughout comments compared to just over 25 by men (Figure 2). The number of comments in which these features appeared was identical for male and female. Females typically used digital cues including excessive punctuation to better convey emotion online.

Next, we considered influencers’ usage of capitalized words within sentences. We found that female influencers were more inclined to capitalize individual words or phrases when replying to comments. Women often capitalized words of encouragement like “good job” yay” or “yesss”. Conversely, men rarely utilized the capitalization of words.

Figure 3: Capital Letter Usage: Male vs Female Influencers

The capitalization of words (particularly for emphasis) was used by females at a higher rate than their male counterparts. Whereas women did this over 100 times throughout our data, men did not even reach a count of 5 (Figure 3).

Finally, we looked at the pet names influencers used when responding to comments. Female fitness influencers often used words such as “girl,” “queen,” and “babe” to address their followers, whereas males used terms like “man,” “buddy,” and “mate” to address their followers in a similar supportive fashion. Figures 5 and 6 display the overall comparisons of the four linguistic features’ rate of appearance in 10 comments written by the male and female social influencers.

Figure 5: Usage of Linguistic Features of Solidarity: Male vs Female Influencers
Figure 6: Usage of Linguistic Features of Solidarity by Percentage: Male vs Female Influencers

We observed that females used pet names more frequently than males, but the difference was not as large (Figure 7). 

Figure 7: Pet Name Usage: Male vs Female Influencers

 

Discussion and Conclusions

There are four key insights that summarize our research results.

First, by taking a closer observation at the types of emojis male influencers used, we found that males usually used bicep emojis whereas females did not use them at all. Females generally used more emojis across all emoji categories. However, by narrowing down to a more specific sub-parameter within symbolic emojis, we observed that males were in fact using a different tool to strengthen their relationship with their predominantly male fans. 

This insight suggests that in CMC, both males and females likely strive to establish solidarity with their fans but through different linguistic tools. On social media platforms, influencers of all genders are driven by financial motivations to attract viewers by crafting themselves as more responsive and supportive than their competitors.

Second, the nature of the male influencers’ comments was more action-oriented than that of female influencers’ comments. For example, males often posted comments such as “Keep going” and “Well done!”, whereas females often posted gratitude-expressing, emotional comments such as, “Thank you!!!” and “ILY MY QUEEEEN”.

This second point illuminates that most of these interactions took place between same-sex followers and influencers. This phenomenon could be attributed to the fact that the fitness objectives of the videos were inherently geared to target the followers of the same sex as the influencers. For example, we noticed that the majority of the videos created by female fitness stars tend to have titles such as, “Intense Glute Workout”, but males posted videos with titles like “Build a Bigger Chest”. These fitness videos align the body areas that respective genders tend to visually prioritize when developing their body muscles. In general, females are more self-conscious of their leg and glute areas whereas males typically focus on building the size of their upper body.

Third, we observed a dichotomy of ‘emotional vs calm’ which is a digital adaptation of the ‘report vs rapport” model. In particular, male influencers’ average length of comments is significantly less than female influencers’ average length of comments. The male influencers’ responses were calmer than those female influencers. We think this ‘emotional vs calm’ dichotomy is a formal theorization of what computer-mediated gender communication can look like in the context of our digital influencer study. Our research also invites further studies by future socio-linguistic scholars interested in the intersection between gendered communication and online social media platforms.

Lastly, with male influencers specifically, we observed that those with a smaller following responded more frequently to comments than those with a larger following. Once reaching a certain level of popularity (over 1 million), males responded less frequently. We theorize this is because males use more feedback only before their platform grows to a certain level of popularity. Given that our study only examines 20 social influencers on YouTube, we’d like to invite future researchers to conduct more studies in these areas.

In short, our research study shows that females are predominantly more expressive than males across all 4 linguistic categories, but males have more frequently used bicep emojis in particular. In addition, even though females’ responses were visibly more expressive in terms of the frequency and variety of emoji usage, both males and females were pursuing the same purpose of establishing solidarity with their fans, by using different tools.

We argue that the Tannen model is being applied differently in the context of computer-mediated communication and the nature of social media, as social influencers, whether male or female – are in positions to appeal to their general audience. We also propose the “emotional vs calm” dichotomy observed from gendered communication in online platforms and invite further research to be done in this area.

Among several, one limitation of our research is that we did not incorporate the nature of the followers’ comments that the influencers responded to. In general, we observed that most viewers’ comments were positive, grateful, and supportive. This research invites future studies to undertake how the responses would look different towards comments that are hateful or negative. In addition, more studies on how non-famous males and females differ in their digital communication on social online platforms are needed.

 

References

Bamman, D., Eisenstein, J. and Schnoebelen, T. (2014), Gender identity and lexical variation in social media. J Sociolinguistics, 18: 135-160. https://doi.org/10.1111/josl.12080

Fox, A. B., Bukatko, D., Hallahan, M., & Crawford, M. (2007). The Medium Makes a Difference: Gender Similarities and Differences in Instant Messaging. Journal of Language and Social Psychology, 26(4), 389–397. https://doi.org/10.1177/0261927X07306982

Herk, G. V. (2018). Gender. In What Is Sociolinguistics? (pp. 96-116). Wiley Blackwell.

Lakoff, Robin. 1975. Language and woman’s place. New York: Harper Colophon Books.

Sherman, L. E., Michikyan, M., & Greenfield, P. M. (2013). The effects of text, audio, video, and in-person communication on bonding between friends. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 7(2), Article 3. https://doi.org/10.5817/CP2013-2-3

Tannen, D. (1990). “Put Down That Paper and Talk to Me!”: Rapport-talk and Report-talk. In You Just Don’t Understand: Women and Men in Conversation (pp. 74-95). HarperCollins.

Wolf, A. (2000). Emotional Expression Online: Gender Differences in Emoticon Use. CyberPsychology & Behavior, 3(5), 827–833. https://doi.org/10.1089/10949310050191809

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“Of course, right” and “I was just asking to ask”: Women’s Relationship With Cooperative Language and Their Perception

Zoe Curran, Emmeline Hutchinson, Rylee Mangan, Kamiron Werking-Volk

Why do we like Elle Woods from Legally Blonde? Why do we dislike Miranda Priestly from The Devil Wears Prada? Of course, part of it is because that is who the movie tells us to like and dislike, but is another aspect of that how they use language?

Based on existing knowledge that men and women use communication differently, taking divergent paths to accomplish tasks, we sought to determine how these variations distinctly affect men and women. We focused specifically on the effects on women and how their language use changes their perception. Are they the heroine or the villain? Are they the sweetheart or the b*tch? Our study examined the representation of women in the media and explored the implications of cooperative conversational styles on a woman’s perceived image.

We predicted that the way women in movies use language to facilitate, or inhibit, conversation contributes to their perception in aspects that do not affect men. Based on scenic analysis and tracking of key features, we found a correlation between the characters’ use of cooperative linguistic features and their representation in the film that may be integrated into everyday life.

Introduction and Background

Did you know that women are 33% more likely to be interrupted when speaking with men? And that men speak almost twice as often as women in formal conversation? As an all-female research group, we wanted to explore why we were being cut off in some conversations and completely ignored in others (read more about this topic here). Previous findings state that females utilize conversational styles that foster connection and community, while males utilize styles that attempt to strengthen their independence and dominance over the discussion’s topics (Ersoy, 2008). We do understand that men and women converse differently, but why did it seem like our communicative style was inferior when it is an attempt to be more engaging?

An explanation to this unbalanced communication might be women’s more active use of minimal encouragers, nonverbal gestures, and agreements that are intended to facilitate conversation but as we experienced, can yield opposite results. We geared our research towards understanding the implications of what we have termed Cooperative Conversation Linguistic Features (henceforth, CCLFs). CCLFs are a collection of words, phrases, and nonverbal gestures that promote a cooperative speaking style to encourage a conversational partner. These features help balance the conversation by allowing the speaker to continue talking. However, a woman’s increased use of these features can render them as a less-dominant speaker who might be inferred as subordinate and less powerful. To determine if there is a relationship between CCLFs and the speaker’s perceived identity we studied how women and their control, or lack of, the conversation affects their image and in an essence their likeability.

We studied samples of both same-sex and cross-sex conversation groups in popular media. Although movies are not perfect depictions of real life, stereotypes are often constructed from visible patterns of behavior and actions of real people (Kubrak, 2020). Media characters exaggerate the usage and effect of these linguistic features in a manner that can be studied effectively. We hypothesized that female characters’ increased usage of CCLFs will be associated with perceptions of decreased power, confidence and intelligence. We believed it would also be associated with increased likability in the eyes of the audience and/or their conversational counterparts.

Methods

High-stakes conversations between female and male counterparts in contemporary films where there was either a negotiation, conflict or high-profile discussion were analyzed. Our chosen films included The Devil Wears Prada, The Proposal, Erin Brockovich, Fargo, Legally Blonde, and The Social Network. Eight female characters from a total of six films were examined and individually identified as cooperative or uncooperative roles. These characters included iconic figures such as Elle Woods, the protagonist in Legally Blonde, who was coded as highly cooperative, versus Miranda Priestly, the antagonist in The Devil Wears Prada, coded as highly uncooperative.

We counted the number of CCLFs and uncooperative actions (henceforth, UAs) displayed by female characters. CCLFs included minimal encouragers and cooperative overlap, which we defined as words or phrases that serve to promote intimacy, support the conversational partner and indicate encouragement. Another CCLF of interest was cooperative nonverbal cues like making consistent eye contact, nodding, leaning in and making supportive hand gestures. Our last CCLF was facilitating questions, which we defined as any question that served to stimulate conversation, support the conversational topic or encourage the conversational partner. In order to have a full picture of how cooperative vs noncooperative characters are constructed in film, we also documented the number of UAs. These were defined as verbal and nonverbal communication that was disruptive or uncooperative in nature, such as changing the conversational topic, not responding, disruptive interruptions, lack of eye contact, walking away, or arguing with the counterpart’s motives or ideas. We adopted many of these features from Selma Ersoy’s work on collaborative versus competitive communication styles (2008) and added other components we felt assisted or inhibited conversation from our own experiences and the experiences of peers.

Read more about the difference between cooperative overlap and interrupting here!

Quantitative methods were used to calculate the frequency of CCLFs and UAs for each character. Qualitative methods were used to evaluate any unique features of the specific conversational styles of the characters and to make note of how the character of interest was perceived by other characters in the scene.

Results and Analysis

Perhaps unsurprisingly, we noticed a dramatic disparity between the ‘cooperative’ and ‘uncooperative’ groups. Across the board, the women in the cooperative group used the CCLFs at a greater rate. These women also used the uncooperative actions at a substantially lower rate than the uncooperative group: the cooperative group only using them three times in all of their scenes. Much differently, the women in the uncooperative group frequently used the UAs at a total of 17 times. Additionally, the women in the uncooperative group rarely used CCLFs to foster cooperative conversation. Only one uncooperative character used these features at all, for a total of three uses.

Since we were watching movie scenes of various lengths to collect data, we found it important to ensure that the scene length was not skewing our information. To avoid this misrepresentation, we converted the number of features used to the rate the characters used them. This information was calculated as the specific feature usage per minute. We found that Erica Albright and Marge Gunderson were standouts in their high rate of CCLF use at approximately 8 and 7 per minute respectively. Simply put, Erica would use a CCLF every seven and a half seconds in a conversation, and Marge every eight and a half seconds (find our example scene with Erica here). The women in the uncooperative group had a much lower use of CCLF’s per minute, with all but one character using 0 per minute.

Figure 1: Characters’ CCLF Use Per Minute. The x-axis includes the women involved in the study separated by an empty column “—”. The separation indicates the distinct groupings of these women in the cooperative (left) and uncooperative (right) groups. The y-axis measures the CCLFs used per minute by the women. The women in the cooperative group overall used CCLFs at a higher rate per minute.

We also converted the uncooperative actions to a use per minute rating and found that characters such as Vivian and Erin (uncooperative group members) had the highest rates of use at approximately three and two per minute respectively.

Figure 2: The Characters’ Rates of Uncooperative Action Usage per Minute. The x-axis includes the women involved in the study separated by an empty column “—”. The separation indicates the distinct groupings of these women in the cooperative (left) and uncooperative (right) groups. The y-axis measures the UAs used per minute. The women in the cooperative group used UAs much less frequently than the women in the uncooperative group.

Overall, our data showed that the cooperative group had a higher rate of CCLF use than the uncooperative group, comparing an average of 4.5 features per minute to 0.175 features per minute.

Figure 3: The Average Use of CCLFs and Uncooperative Actions (UA) by the Cooperative and Uncooperative Groups. The x-axis shows the two categories of women in our study: cooperative and uncooperative, and the y-axis indicates the number of features used per minute by the groups. The units of measurement are the number of features used per minute. The cooperative group used a dramatically higher frequency of CCLF features than the uncooperative (4.5 per minute vs 0.175 per minute). Also, the cooperative group had a lower rate of Uncooperative Action use compared to the uncooperative group (0.38 per minute vs 1.82 per minute).

The opposite was found with the uncooperative actions, with the cooperative group using them much less frequently at an average rate of 0.38 per minute, compared to the uncooperative at 1.82 per minute. These stark differences can be more clearly described as the cooperative group using CCLFs at a rate 26 times that of the uncooperative group, and using UAs at a rate about 5 times less than the uncooperative group.

Discussion and Conclusions

As for how the use of CCLFs and UAs relates to perception of the character we noticed a common connection between the use of CCLFs among characters that the audience is supposed to like, the people we are supposed to root for, as well as a connection between the characters who used more UAs and their positions as villains in the narrative.

To paint a clearer picture let’s look at the movie Legally Blonde. Elle, a character from our cooperative group is the hero of the movie, while Vivian from the uncooperative group is one of the main antagonists. We as an audience are not supposed to side with Vivian until she changes her ways and becomes friends with Elle. (See our example scenes with Elle and Vivian). This is not a motif isolated to Legally Blonde since the same can be seen in The Proposal. Sandra Bullocks’ character Margaret Tate is called a “witch” and a “monster” by her peers, sending a clear signal to audiences on what to think of her character. It is not until her character’s journey to her relationship with the male lead, Andrew Paxton, and her becoming somewhat nicer that she gets praise and a happy ending.

In our sample these same motifs simply did not exist for men. A prime example of this being Mark Zuckerberg in The Social Network, a character that practices disruptive communication. He is offstandish and objectively unkind in the opening scene and throughout the movie, adopting many of the UAs we identified, but at the end of the movie he is still praised. The audience sympathizes with Mark and despite his flaws he is not given a redemption arc in his movie, he is simply allowed to exist. The male characters we observed did not have to be perfect or traditionally nice to be liked. We believe that this may reflect a broader standard that women are held to in the real world. Our research speaks to how movies shape us and give us hints about who we are supposed to be.

For more insights on how movies shape us, watch this TEDTalk.

Although our study stuck to a relatively strict gender binary and focused on white, middle to upper class, straight coded characters, we feel it brings up valid questions about the perception of women and what standard women are held to both in media and in real life.

 

References and Used Sources

Borresen, Kelsey. “How To Know If You’re An Interrupter Or A ‘Cooperative Overlapper’.” HuffPost, HuffPost, 4 Mar. 2021, www.huffpost.com/entry/interrupting-or-cooperative-overlapping_l_603e8ae9c5b601179ec0ff4e.

Ersoy, S. (2008). Men compete, women collaborate. Kristianstad University: Language and Gender. http://www.diva-portal.org/smash/get/diva2:231309/FULLTEXT01.pdf

Fincher, D. (2010). The Social Network. Columbia Pictures.

Kubrak, T. (2020). Impact of Films: Changes in Young People’s Attitudes after Watching a Movie. Behavioral Sciences, 10(5). https://doi.org/10.3390/bs10050086

Luketic, R. (2001). Legally Blonde. Metro-Goldwyn-Mayer & Marc Platt Productions.

Stokes, C. (2012, November). How movies teach manhood. https://www.ted.com/talks/colin_stokes_how_movies_teach_manhood

Susan Chira. (2017, June). The Universal Phenomenon of Men Interrupting Women—The New York Times. Retrieved March 17, 2021, from https://www.nytimes.com/2017/06/14/business/women-sexism-work-huffington-kamala-harris.html

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Laugh Now… Because It Won’t Be Funny Later

Angelena Escobar, Debora Gotta, Lilly Khatirnia, Talia Kazandjian

Comedy and laughter are often viewed as universal languages. It is said that comedians have the capacity to produce discourse about the darkest and most challenging aspects of life, all the while making us laugh. This meant nothing was really off the table for comedians in the 90’s and early 00’s. However, in the last five years especially, with the massive rise of social media and cancel culture, we have seen both celebrities and private citizens being reprimanded or heavily criticized for their current or past actions. Comedians, especially, who were appreciated for their dark and uncensored humor, are now having to rethink their entire routine. Keeping that in mind, is comedy still regarded as it once was or have societal values changed enough to transform the stand up comedy landscape?

Introduction

Figure 1: Kevin Hart

Stand-up comedy is one of the major sources of entertainment. It began to hit the ground running in the early 50’s and 60’s, in which socially aware comedians made their way into the spotlight (Pulliam,1991, pg 164). However, stand-up comedy did not reach its peak until the 1970’s. The main purpose of comedy was to showcase current events, culture, and the personal lives of comedians (Zoglin, 2009, pg. 3). This essentially meant that a large amount of what was taking place during a certain point of history would be a focal point of comedic routines. Comedians also implemented their personal stories as a part of their jokes. While comedy has obviously been used for comedic purposes, it has been a factor in social change as well. In “Stand-up Comedy as a Tool for Social Change”, Manwell claims it is important to draw attention to negative stereotypes to be socially progressive. He emphasizes how humor that “draws criticism for being offensive and for perpetuating negative stereotypes” is, in actuality, progressive, because it pushes the boundaries of what is socially acceptable (Manwell, 2008, pg. 50). While Manwell piece was published too early to comment on the age of social media and social awareness, the implementation of stereotypes into comedians’ stand-up routines is crucial as it allows the audience to be more socially aware.

Background

Although there has been some research done on the topic of comedians using language, there has not been research done focusing on how comedians use language to create a comedic effect. Stand-up can be succinctly described as an Anglo-American form of comedy where a solo performer aims at repeatedly making her co-present audience laugh, primarily through personal narrative. Comedians manipulate language and use comedic elements to generate humor.

Methods

Our project was consistently developing the more information we found; therefore, we continued to tweak and modify our research question. At the beginning of our analysis, we sent out an anonymous survey to our friends and family. We received a total of 62 responses from individuals aged 18-49. There were multiple questions in that survey that were not as helpful as we continued working on our project; however, one was very important. We asked our survey takers to name both male and female stand-up comedians, and as it is seen within the word cloud: Tiffany Haddish, Amy Schumer, Dave Chappelle, and Kevin Hart were the most popular ones. Seeing that Kevin Hart garnered 50% of the responses when asked for male comedians, it was a determinant in deciding which comedian to focus on and what kind of research we can do based on him.

Figure 2: A word cloud containing the names of the comedians named by the participants. The size of the name corresponds to the frequency the comedian was listed.

After deciding that we would work on Kevin Hart, we started to explore his past shows and decided to focus mainly on Seriously Funny, I’m a Grown Little Man, and Zero F**ks Given. These shows span a period of eleven years where we are able to observe and analyze the evolution of Kevin Hart and how/if his comedy have been influenced by fast changing social norms and values.

Figure 3: I’m A Grown Little Man (2009), Seriously Funny (2010), Zero F**ks Given (2020)

For our work to become more organized, we also decided to divide the jokes we looked at into four categories. It starts with the jokes being self-centered or other-centered, then within that there is a range of it being based on experience or appearance. Self-centered experience jokes are about Kevin Hart’s own personal experiences; Self-centered appearance jokes are about Hart’s appearance or how he is perceived outwardly; Other-centered experience jokes are about other people’s or a group of people’s actions or experiences; Other-centered appearance jokes are about how they look when they behave or are about other outward appearance features. The chart below shows the different topics of jokes Kevin Hart discussed throughout his comedy shows.

Figure 4: A visual representation of the types of jokes analyzed

Results and Analysis

The Use of Other-Centered and Community Based Jokes vs. Self-Centered

In I’m A Grown Little Man, Hart seemed to be more focused on community-based jokes. He used examples of the people he met and recreated scenarios with those individuals to portray how they acted in certain situations. One example is a specific scenario in which Hart imitates rappers and thugs to humor his audience– reflecting back to the theory of other-centered jokes. Hart made little jokes about his personal life because people weren’t as sensitive about certain topics/groups/stereotypes as they are now. Another example is the joke Hart made about a previous girlfriend of his that was White. He talked about her dad and turned it into a racial joke which the audience then took as humorous but would probably offend some people today. Hart acts out his jokes using code-switching and he indexes various communities by using alternate slang. He performs tone & slang differently when making jokes about the Black community compared to language used to connect with the White community.

Kevin Hart – Thug Laugh

Kevin Hart – Rich White Guy Laugh

In past comedy routines, Kevin Hart often used other-centered jokes in which he would use other communities as the primary focus of his jokes. While not all of Hart’s jokes were offensive, there were some that would not currently be socially acceptable. Hart has exhibited change in his most-recent stand-up, Zero F**ks Given, he tends to focus on himself and his family rather than making others the center of his joke. This not only depicts how Hart has evolved, but also showcases how the norms of what’s acceptable in comedy and society has been redefined. Considering the fact that this generation is more aware and sensitive to offensive topics, comedians are often pivoting and reconstructing their comedic routines in order to suit everyone. In the segment posted below, Hart uses intonation when telling the story about his daughter liking different guys every week. His voice rises and falls depending on what part of the story he is sharing. When name calling his daughter or son, he is relatively flat and speaking matter of factly and during other parts, he’s more animated and eccentric. Whereas before, the more offensive statements were other-centered, now the more “risque remarks “ are about him and his family. This is a significant sign of evolution in his routines reflecting social norm changes. The omission of teasing other people can stand as evidence that Hart has transformed his routines and has decided to become more adaptable to the times.

Kevin Hart – My Children

 

The Delivery of Jokes: No Filter vs. Socially Aware

This section of analysis focuses on Seriously Funny, Hart’s second recorded show in the touring part of his career. In this stage, he had a nonchalant attitude towards his jokes: no prevalent social awareness, no expected repercussions–and seemingly no filter–joking about any topic. Later, he defended these offensive jokes by saying “funny is funny”. To an extent, he’s correct as jokes now deemed offensive were successfully funny back then, in terms of success being measured by the intensity-and-length-of audience laughter. The change in the jokes he said is a great example of how societal norms/values have changed over time. What was accepted then, isn’t accepted now, what was funny then is now offensive. The following video is a segment from Seriously Funny. Hart’s joke is successfully delivered, and he effectively creates comedic effect through his use of intonation (the audible changes in his voice for emphasis), indexicality (personifying other people), and body gestures (for visualization of the story).  When he jokes about his son’s first gay moment, he clearly impersonates his son, the other child, and the woman who intervenes. Though his voice does not change much, unlike other segments he has done, his acting is very clear and he is able to distinctively act like the characters in his story through body motions. When he behaves like his son, he taps into how he described his son earlier in the show. He had claimed his son was, “a dumb kid that doesn’t really know what he’s doing” and shows this by waving his arms in all directions with no real or distinct rhythm. When he talks about the women who interferes, he becomes very calm and speaks in a standard tone of voice suggesting that there was no apparent problem between the two children. Lastly when he indexes his-self in that moment, he returns to an angry defensive tone and body language. Though this joke was comically effective back in 2010, this joke in particular has led to backlash–ultimately leading to Hart stepping down from being the 2019 Oscars Host. 

Watch the video and determine whether or not a joke like this would fly in current times: Kevin Hart – “My Son’s First Gay Moment” Seriously Funny (2010)

Contrastingly, in his latest comedy special, which aired in 2020 after his Oscar scandal, Kevin Hart is much more careful and aware of what he says and the types of jokes that he makes. Whereas before, the jokes were just delivered, now he actually uses self-repair in order to correct what he says or “soften the blow”. In the following video, there is an instance when he is about to make a joke on greeters, he pauses himself and makes a premise that he “… has nothing against greeters…” He makes it clear that he understands that it is an important and useful job, but it is something he does not have to or want to do. By making these comments, he’s able to go on with the joke, having established the foundation that he respects the occupation and does not see it as a bad thing. This can stand as an example of disaligning responses where Hart is able to “… revise or back down from… prior actions in order to permit preferred responses to be produced instead” (Whitehead, 2015, pg 4). In a time where there is heavy criticism to any kind of offensive remarks, making those preemptive comments or jokes about “cancelling” itself may make it so that those viewing the show don’t take it to heart as an offensive statement but rather a simple joke. He is mindful and concerned with how the wider/mainstream audience will interpret his joke. He is more socially aware of potentially offensive comments in his jokes. He is self-censoring which initiates self-repair. He does this by using specifically the use of intonation and indexicality to defer between the times that he is speaking as himself and the “persona” of those that may be after him post this joke. For example, when he impersonates the lady that is filming him as he eats his burger in front of McDonalds, he acts aggressive, angry, and accusatory. His hand is in front of him as if he is holding a phone and filming and his eyes are wide open (kind of as if he were crazy). When he is back to being himself he just describes what he did in a more relaxed tone and continues with the joke.

To further demonstrate what we mean, here are two segments from his latest comedy show attached below, where Kevin Hart makes the extra effort to communicate that he is not being offensive or seriously making a statement.

“Kevin Hart Loves Wal-Mart Greeters” Zero F***ks Given (2020)

“Why Kevin Hart Hates Snitches” Zero F***ks Given (2020)

 

Discussion/Conclusion

Our research aim was to understand whether societal norms have changed in the past 10 years by investigating one of comedy’s biggest stars, Kevin Hart. Starting from Seriously Funny to Zero F*cks Given, we observed an evolution in Hart’s shows–leading to conclude that societal norms and values have indeed changed. What was once received as humorous and funny may now be unacceptable by the mainstream. This generation is much more vocal about the types of jokes and statements one can make about a community. We came to this conclusion by analyzing the language used by Hart. By using different communication tools, both verbal and nonverbal, (code switching, indexicality, intonation, self-repair) we gained a greater understanding of societal value changes and impacts on systems within society, like entertainment. Despite his controversial past, Kevin Hart remains incredibly popular (as was evidenced by our survey and his record breaking show attendances). As we conclude this post, we wonder: Would you also agree with our conclusion? Where do you think the relationship with comedy and risqué remarks is headed in the future?

 

References

Manwell, C. F. (2008). STAND-UP COMEDY AS A TOOL FOR SOCIAL CHANGE. https://lsa.umich.edu/content/dam/english-assets/migrated/honors_files/Manwell%20Colleen-Stand-Up%20Comedy%20as%20a%20Tool%20For%20Social%20Change.pdf.

Pulliam, G. (1991). Stock Lines, Boat-Acts, and Dickjokes: A Brief Annotated Glossary of Standup Comedy Jargon. American Speech, 66(2), 164-170. doi:10.2307/455884

Whitehead, K. (2015). Everyday Antiracism in Action: Preference Organization in Responses to Racism. JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY, 34(4), 374-389. http://dx.doi.org/10.1177/0261927X15586433 Retrieved from https://escholarship.org/uc/item/7767x91b

Zoglin, R. (2009). Comedy at the edge: how stand-up in the 1970s changed America. Bloomsbury USA.

 

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What is the Situation with Celebrities’ InToNaTiOn?

Juan Alvaro, Darshini Gupta, Lauren Tropio

In today’s day and age, a social media presence has become not only essential but  also a platform that defines us as individuals. In February of 2019, a statistic  showed that 90% of adults ages 18-29 use social networks because it is the new
“norm”. Up until the creation of more popular apps and interactive websites, social media was arguably far from a necessity and was seen as a way of  communicating or staying up to date with current news.

Now due to this shift, social media is seen as a defining characteristic of a  business or person. Also, interactive media and networks have given  bloggers, celebrities, etc credibility and a larger audience to influence  and illustrate their linguistic style that varies across written and  recorded platforms. Studying the individuals that society defines as “influencers” reveals the transformation of identities, and patterns of  intonation that take place on various social media, with these “celebrities” altering these tendencies between each media platform.

To get a better idea on how different intonation patterns can convey personality,  and based on the responses we got from a survey distributed to college aged  students, we decided to look more in depth on three people: Kylie Jenner, Jojo Siwa,  and David Dobrik. These three different personalities offered a different aspect of  intonation patterns, Kylie Jenner representing little variation, Jojo Siwa  representing a different approach with many variation patterns, and David Dobrik  being somewhere in the middle. We studied these individuals by going through their  content on various platforms (Youtube, Instagram, Twitter, etc). By studying these  influencers across the intonation spectrum, we can get a sense of what aspects of  intonation patterns can be used to display a specific persona.

Kylie Jenner

The first person we decided to look at was Kylie Jenner. She  started out by being a part of the Kardashian/Jenner family  and a reality show from the young age of 9, now is known  around the world as one of the youngest billionaires and has  many business ventures as well! She has been in the limelight and been immersed in the influencer culture for a large part of her life. She is one of  the highest paid influencers and her millions of followers across platforms makes  her a perfect candidate to study. 

Looking through her Youtube videos, the first thought that stood out was her use of  uptalk and vocal fry. ​In this video, one can see that her speech is characterized with a rising  pattern at the end of her sentences, which is uptalk, and how she also uses a very  low register in her speech giving a creaky sound which is vocal fry. Even the  comments on her post took notice of her use of uptalk and not surprisingly were  divided on it, some thinking it sounded more professional while others were  bothered. Another viewer also pointed out how all of the Kardashian/Jenners speak  this way and though this could just be a part of Kylie’s linguistic style it could also  be a way for her to solidify part of her identity, which has been associated with this  family her entire life. Another thing that stood out studying her videos was Kylie’s limited variation in  her intonation. ​In this video, even when Kylie is making exclamations like “7!” or “ooooh what’s a 7 pump” her intonation does not change much and it. It almost feels  like there is more excitement or variation in my transcript of those comments! In a  more recent video, she goes on to explain how she restrains her personality or  almost plays a character in videos and on social media deliberately, in which she  could possibly be using intonation as a tool to show less of her personality while still  giving new content.  Looking through her Instagram posts, we noticed that she portrays a very similar  intonation pattern through her captions. 

By using no capitalization and very few exclamation points and punctuation in her  posts, she is able to convey a certain tone with an unwavering pitch, which is  similar to her speaking style.  

David Dobrik

Many may know him for his infamous 4 minute and 20  second vlogs or his debut on an application called Vine in  2013, but today he is recognized for his presence on various written and video platforms. He is probably more successful than I will ever be in my  lifetime, having millions of followers across, YouTube,  Instagram, Twitter, and Tik Tok. David also has a  networth of over 15 million at the age of 24.

When it comes to his identity and how he portrays himself across tweets versus his  vlog content, one would potentially think he was two different people. In his written  work David used capitals throughout. “CHIPOTLE NAMED A BURRITO AFTER ME” is  an example of how explosive he can be. Or “NOT WITH THAT ATTITUDE”  demonstrates that aggressive identity one would think he would have. When  reading either of these, one may even interpret these tweets as YELLING at you!

On the other hand, after observing hours of videos produced by David, there were very few instances where he continued this kind of eruptive intonation. The only  times he changed his tone or portrayed himself as “loud” was when he was  laughing. To better understand where his inflection lies in his videos, we used Audacity to visualize where this burst of intonation exists. Below you can see a clip of David speaking where the loudest and tallest waves represent him laughing. The in  between represents his normal speaking voice.  

We found David to be the most inconsistent when it came to his intonation, which is  why we also saw him as a good middle ground between Kylie and JoJo. Having  someone like David Dobrik, he is a good individual to have as the intermediary  control. He shows viewers how much intonation JoJo Siwa has and how little  intonation Kylie Jenner has. He originally identified as a YouTuber, but I believe as he tried to transition to other  platforms his identity became inconsistent. It seems he uses capitals in his written media to grab attention more than showcase who he is as a person. His random capitalizations and phrases where he seems to be yelling at his audience, could be a publicity stunt more than an identity trait. He does have moments of strong intonation variation but it does lack that sense of constant variation like his  written platforms would infer. Maybe it is time someone takes his computer and  turns his CAPS lock OFF!  

Jojo Siwa

Jojo Siwa or more formally known as Joelle Joanie Siwa is a  well known American dancer, singer, actress on  Nickelodeon, and also an infamous influence on YouTube.  She has 12 million subscribers on Youtube and about 10  million followers on instagram. Jojo Siwa began to attract  the public’s eye in 2014 at the age of 11 years. Since then she  has had hundreds of millions of views on her videos and is known for being very outgoing and extroverted with sporadic behavior and  varying intonation in her voice. Her pitch varies in order to allure the audience and  attract their interest so that she can get them to invest their time on her. 

She shares very similar styles of intonation across both video and written platforms as she uses lots of exclamations in her statements. In one of her most recent videos, Jojo Siwa mentions the word “Tie-dye” twice in consecutive order, however uses two different variations of intonation. The first time she uses the word, she includes rising intonation and the second time the tone is falling intonation. She proceeds to say the word a few more times throughout the video with varying types of intonation. What’s also worth mentioning is that Jojo Siwa tends to lengthen the duration of her vowels and adds nasality in her voice, however that may be due to the nature of her vocal chords. She employs all these  different linguistic aspects in order to promote her character as an influencer and  attract her audience to purchase her merchandise. This compulsive behavior really  targets and pulls the interest of many as comments mention the love for the way  she behaves.

Similar to her voice on video platforms, she tends to add all capital lettering in her  posts and repeats letters to add emotional appeals. Her social media accounts all  carry the same text aesthetic involving this very family friendly speech. Her voice is very reminiscent in her tweets and IG messages and wants to persuade people to get  involved in her life. As you notice there are also lots of exclamation marks and use of emoji’s and by her facial expressions, she always appears to give off an ecstatic/ overly-cheery identity/personality. She is meant to appeal to children, which is why  she constantly gives off this radiant energy. 

Overall findings

After interpreting what we observed and our results, the conclusion drawn was  that social media platforms give influencers the chance to expose their pitch range, identity, and intonation variation. This differed between all the celebrities studied. These influencers construct an identity through social media platforms and their  style may shift but it does not always, as it is really dependent on the person.  Intonation is just one of the tools influencers may or may not choose to employ in  their linguistic style and we can see that based on these three personalities. Although intonation is an effective tool to display a persona, it is not always used or  consistent. These influencers choose to embrace their own identity which is best  catered towards the content they are trying to put out. 

 

References

“Kylie Jenner Net Worth”. Forbes. November 1, 2020. https://www.forbes.com/profile/kylie-jenner/?sh=43cb99fc55b5.

“Jo Jo Siwa Biography”. Biography. Biography. Retrieved 24 Dec 2019.

de Aquino Carlsson, A. (2018). Persuasion in social media : A study of Instagram  influencers’ usage of persuasive speech acts (Dissertation).

Ge, Jing, and Ulrike Gretzel. “Emoji Rhetoric: a Social Media Influencer Perspective.” Journal of Marketing Management​, vol. 34, no. 15-16, 2018, pp. 1272–1295., doi:10.1080/0267257x.2018.1483960.

Leskin, P. (2020, February 02). The rise of David Dobrik, a 23-year-old YouTuber worth over $7 million who got his start making 6-second videos. Retrieved  December 12, 2020, from https://www.businessinsider.com/david-dobrik-net-worth-youtube-career-v ine-liza-koshy-2019-9

Pew Research Center. (2020, June 05). Demographics of Social Media Users and Adoption in the United States. Retrieved November 17, 2020, from

Social Media Fact Sheet

Siwa, JoJo. “Its JoJo Siwa”. YouTube. Retrieved September 26, 2020.
WIRED (December 16, 2018). “David Dobrik Answers the Web’s Most Searched Questions”. Retrieved January 31, 2020 – via YouTube.

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Yeah, Um… So Like, Are Filler Words Considered Feminine?

Jennifer Beck, Jaymie Bernardo, Theo Chen, Karl Danielsen, and Calista Eaton-Steinberg

At some point in your life, you have probably experienced the intense awkward silence that comes about when it’s your turn to speak and you have no idea how to respond. Whether you’re not sure how to answer a question or you simply got lost in your train of thought, perhaps you’ve found yourself choosing one of these coping mechanisms to deal with that moment of dreaded stillness in the conversation: (1) you accept the silence and ponder your next move; (2) you fill the silence with filler words to buy time. Filler words such as “like,” “well,” and “um” are a common occurrence for people in conversation who are thinking of what to say. If you pay attention, you might notice that you use these words unconsciously in daily conversation, not even noticing when they slip out.

By observing, collecting, and analyzing video interviews, our study focuses on the correlation between gender and filler words in Californian college students. Studying the use of filler words in different genders of the cis-binary will allow researchers to better understand the way that gender and filler word usage interact. The purpose of this study is to clarify the assumption that women use more filler words than men due to persisting social pressures and the social implications of filler words.

Introduction and Background

Professor Eckert discusses in her linguistic studies that women typically have a different linguistic role in society compared to men (Eckert, 2012, pp. 90). When men speak, they try to keep up a persona that exudes confidence. As filler words explicitly foreground someone’s lack of confidence in speaking – they indicate that the speaker does not feel entirely certain about the things they are saying – men are presumed to more commonly avoid using filler words. In comparison, women generally assume a more mediating role in conversation (Van Herk, 2017, pp.110), so they might be expected to use more filler words.

Finding a connection between gender and filler word usage could indicate that one gender is less affected by the negative traits associated with filler words. In other words, one gender group may feel less social pressure to avoid filler words despite their pre-existing negative implications. Alternatively, one gender might actually prefer using filler words as modes of marking discourse to connect and organize the things they say in specific ways (Divett, 2014, pp. 37-42). A paper in the Journal of Language and Social Psychology found that men and women both use filler words equally when filling pauses, but that women use them more as discourse markers (Laserna et al., 2014, pp. 332-334). In this way, women use filler words to assert their authority in a conversation by directing its path and indicating it is their turn to speak. Due to the unprofessional associations with filler words, we hypothesize that women will use filler words more than men, as women face lower levels of societal pressure to sound professional. They may also utilize these words more often to direct conversation. We conducted a small-scale study of casual interactions between college-age men and women to assess the patterns of filler word use.

Methods

We analyzed 15 interviews of Californian college students posted on college-related YouTube channels. These casual one-on-one interviews asked random students basic questions about their college experiences. We looked at results from women interviewing men and men interviewing women and calculated the number of filler words (including “um/uh,” “like,” “yeah,” “so,” “I mean,” and “you know”) relative to the number of total words spoken.                                                                                                                                        
Results/analysis

Previous research into this topic suggests that women do, in fact, use more filler words than men (Laserna et al., 2014, pp. 332-334). However, as gender roles become less important to our modern society, the previously discovered results may have become outdated. We set out to see if we could reproduce other studies’ outcomes in a modern, progressive college setting, while simultaneously seeking out answers as to what factors could cause the gendered differences in filler word usage.

While our final results matched those of previous studies in confirming a gender difference, the difference we found was not what we expected. Below are a couple of statistics from our data collection:

Figure 1: The most significant data from our research; note the difference between mean and median results.

Looking at the overall ratio result, our results did not support the previous findings on this topic. Women surveyed actually used significantly fewer filler words than men. Looking at the overall total words to filler words ratio, males displayed a 9.651 ratio, while females displayed a 11.885 ratio, showcasing a 2.233 difference in filler word usage between the two genders. Oddly enough, the median of the data contrasted this. The median female used more fillers than the median male. This could potentially mean that men tend more towards extremes, while women speak more similarly across the board. Indeed, one interview with a male revealed the most filler word usage of all interviews, as the male spoke with almost one filler word per five words.

In spite of the inconclusive results of our mean/median analysis, two segments of the data did show a clear trend. Across all interviews, women and men showed preferences as groups for different filler words. Women favored the word “like,” which is increasingly androgynous but still closely associated with the “valley girl” archetype. Men, in place of using the effeminate “like,” preferred words such as “yeah.” It appears that both genders selected their filler words carefully to index different personas, even if they used filler words at similar rates. This means that social pressure is still strongly at play in word choice, even if neither gender has a stronger need for the confidence lent by decreased filler usage.

Both genders together indicated another interesting trend: the presence of two, not one, spikes on the graph of filler ratios. Figure 1 below shows that there is a peak of people using ~6 words/filler word and one of people using ~13 words/filler word. This two-peak system indicates that there are likely two separate modes of speech people use, one casual with a higher ratio of fillers, and one formal with a lower ratio. Filler word use overall is likely distributed across two standard deviations centered at these spikes.

Figure 2: A histogram showing the number of interviews with a certain filler ratio. Make note of the two separate peaks – one at 6, and one at 13.

 

Discussion/Conclusion

Our research shows that the differences in filler word usage across genders are more complex than previous findings suggest. Figure 2 below shows the transcript between two different interviews we observed, both being asked similar questions. You can see the female interviewee produces five filler words out of 43 words total. On the other hand, the male interviewee produces six filler words out of a total 40 words. The margin of filler word usage is slim here. As we mentioned before, females have been found to favor the filler word, “like” while men favored “yeah”. You will note that in this case, the male favored the word, “Uhm.”  While not every male favors the same word, overall data suggests that there is still a generally consistent difference between male and female filler word choice, especially in the use of “like.”

This could be a result of gender stereotypes for speech – “like” and “so” are associated more with femininity, while “um” and “yeah” seem more masculine. There aren’t rules for who can say what, but speech can be very gendered. Part of it might be conscious – for example, males might avoid “like” for fear of sounding feminine – but it might also be a result of who these people are spending time around and what kind of speech they naturally pick up from friends and family.

Figure 3: Transcripts of two interview segments, both involving the opposing gender. Extracted from ProWrite Admissions YouTube channel.

 

It is important to keep in mind that the data used for our results was extracted from online videos of causal speech. Casual speech with a fellow young person allows for a more comfortable setting, therefore allowing for more filler words to be used. Because these videos were spontaneous and filmed, it is also possible that certain participants were more nervous than others, causing them to use more filler words as they collected their thoughts. Some people are more anxious speaking spontaneously in front of a camera, which would definitely affect their mannerisms, while other people might love being filmed and thrive in the same situation, speaking with confidence and ease.

Our current research sought to analyze the long-lived stereotype of women using more filler words than men, which may exist due to the even older stereotype of women having less intelligence. With these results, we come to the conclusion that college-aged males within California use filler words more frequently in casual speech than college-aged women in California. This could result from a number of factors. For one, more male college students are in STEM fields (Blackwood, 2020) where interpersonal skills are de-emphasized, and students might use more fillers. Men could also be more willing to index a casual persona in interviews because there are fewer expectations against their intelligence that they want to combat. With the persisting sociological stereotypes that deem women less intelligent, women have to work twice as hard in order to gain the respect that men have, especially within the work field (Eckert, 2012, pp. 90). Women are held to different expectations than men, which could impede on filler word usage.

Furthermore, a strong negative social stigma exists around young women who use filler words, especially “like.” Frequent use of the word “like” is a characteristic of the valley girl accent, a Californian accent associated with wealthy, unintelligent, and annoying young women. (This NPR article talks about some other ways that women’s language is stigmatized and disrespected). Since women have to overcome these pre-existing stereotypes, it is possible that they consciously work harder at not using filler words.

Should this research be conducted in another state with another age range, or in a more formal setting, the results may differ. However, our data challenges a conventional understanding of filler word use, suggesting that this topic is very complex and requires further investigation. Potential future research could look into formal interviews between an employer and potential employee, and whether this context decreases filler word use, regardless of gender. Research could also look into stereotypes surrounding different filler words, and whether these stereotypes consciously affect filler word use.

 

References

Crimson Education. (2013). Home [YouTube Channel], from https://www.youtube.com/c/CrimsonEducation/about

Divett, S., Duvall, E., Graham, T. Robbins, A. (2014) How and why people use filler words (pp. 35-46). https://schwa.byu.edu /files/2014/12/F2014-Robbins.pdf

Eckert, P. (2012). Three waves of variation study: The emergence of meaning in the study of sociolinguistic variation. Annual Review of Anthropology, 41, 87-100.

Laserna, C., Pennebaker, J., Seih, Y. (2014). Um . . . Who Like Says You Know: Filler Word Use as a Function of Age, Gender, and Personality. Journal of Language and Social Psychology. 33(3), 328-335. DOI: 10.1177/0261927X1452699 OR https://www.researchgate .net/publication /27 5005568_Um_Who_Like_Says_You_Know_Filler_Word_Use_as_a_Function_of_Age_Gender_and_Personality

ProWrite Admissions. (2017). Home [YouTube Channel]. YouTube. Retrieved November 16, 2020, from https://www.youtube.com/channel/UCpjORe_vOMevyxImw90igLw

Van Herk, G. (2017) Gender. What is Sociolinguistics? Wiley Blackwell. (pp. 97-115)

W.K.C., Kate Blackwood. (2020, July 1.). Gender gaps in STEM college majors emerge in high school. Cornell Chronicle. https://news.cornell.edu/stories/2020/07/gender-gaps-stem-college-majors-emerge-high-school

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Turn on Your Camera, Foo : Slang and Visual Cues in the Classroom

Jiajun Weng, Chris Lam, Christine Chang, Terri See Lok Ho, Wei Lin

Have you ever wondered whether understanding what your classmates are saying and the seeing their cameras is essential to succeed in the course?

You’re not alone.

During this special period, education has primarily moved on to online. Many international students from UCLA taking online courses claim that they feel alienated in the class because they cannot see their classmates when their classmates are talking, and they sometimes cannot understand the online slang used by their classmates. Does the usage of online slang and lack of visual cues truly impact their learning experience?

For finding out the answer to this question, we conducted a study to investigate how the use of slang and the lack of visual cues contribute to international students’ comprehension difficulties and their feelings of alienation. The survey sample comprised entirely of UCLA students. By analyzing the data, we found that interestingly, their feeling of alienation was not affected by usage of online slang nor lack of visual cues. Furthermore, we found that their comprehension was not associated with inclusiveness. That is, it shows that one can still succeed in the class even if one feels alienated.

Introduction

International students in an English-speaking country such as the United States face various challenges related to language. For instance, they struggle with the use of slang and cultural references in a classroom setting. In Bradford’s research, he found that “Teaching colloquial speech in any language can be important for acquisition and assimilation into the language’s cultural group” (Bradford, 2010). In a separate study, Albalawi found that some L2 learners indicate learning slang is helpful for students to fit in socially in college and gain confidence (Albalawi, 2014). Both articles demonstrate that learning the slang of other cultural groups is a crucial tool for L2 learners to master if they want to become more assimilated. However, some of these difficulties in comprehension can be overcome by implicit cues such as facial expressions and gestures (Sueyoshi & Hardison, 2005).

A comment about Figure 1 below showing the breakdown of UCLA students and their experience with English. Moving onto online learning platforms during the global COVID-19 pandemic, international students face new challenges like adapting to the lack of visual cues — such as facial expression and gestures — as well as the colloquial way people speak during Zoom lectures. As a consequence, international students’ ability to comprehend course materials may be compromised by the lack of social cues. With limited understanding of course material, these students could subsequently feel disconnected, or even isolated from the class, and hence disengaged with the course.

International students who engage primarily on non-English social media platforms, such as Wechat, Weibo or KakaoTalk, may have found it more difficult to navigate higher education in this virtual environment. Within this experimental study, we investigated how the use of slang and the lack of visual cues contribute to international students’ comprehension difficulties and their feelings of alienation. Specifically, we expected to find increased feelings of alienation and reduced engagement among international students in the face of online English jargon and little visual cues. However, we hypothesized that the use of slang should not significantly impact students when visual cues are present in the recorded lecture because non-verbal communication can be an important source of motivation and concentration for students’ learning as well as a tool for taking and maintaining attention (Zeki ,2009).

Figure 1: UCLA students’ distribution

 

Collecting Data: Setting up a Classroom

An experimental study was conducted to test our hypotheses about how the manner of people’s speech during the lecture and visual cues (i.e., facial cues and gestures) interacted with each other to influence international students’ understanding of the course materials and their feeling as a member of the class. In the current experiment, we showed our 16 international student participants one of the four Zoom lecture recordings in which we systematically varied the manner of speech of people in that class, as well as the presence of visual cues. To manipulate people’s manner of speech during class, the student confederates discussed the class material in standard English or in a colloquial manner that involved the use of English slangs, like “btw” or “hella”. To manipulate the presence (or absence) of visual cues such as facial cues and gestures, confederates in the current class video will either turn on or off their camera and showed their face and hand movement during the lecture recordings. Please see Table 1 for a demonstration.

Table 1: Matrix of variables and samples of corresponding experimental script

 

After the participant watched one of the four mock zoom lecture recordings, they were instructed to complete a questionnaire that assessed their understanding of the lecture content, which is about this basic psychological phenomenon called the cognitive dissonance theory. Besides the objective measure of participants’ understanding of the class material, their subjective perception of how well they understood the lecture was also assessed. Finally, we measure how much these participants feel like a member of the class and the likelihood of engaging with the lecture if they were present in the Zoom meeting room.

Results and What They Mean

Figure 2: Video On and using Slang trail; participants’ feeling of alienation

 

Our findings supported the initial hypothesis that having video on in these online lectures affected students’ level of comprehension. However, there wasn’t a statistically meaningful difference in feelings of exclusion. In particular, the analysis showed that there was a meaningful difference between the results of the survey question regarding subjective comprehension conducted with the students who watched the lecture with video and without video, regardless of whether there was slang or standard English used. However, even by looking at Figure 2 and Figure 3, it is clear that students felt excluded either way.

Figure 3: ’Video Off and using Slang trial; participants’ feeling of alienation

 

The same was true regarding our initial hypotheses about slang usage. The study showed a statistically meaningful difference in level of self-reported comprehension, but not on the feelings of exclusion. Visually comparing Figures 2 and 4 shows that the responses to the question about alienation were not meaningfully different when video was on vs. off in Figures 3 and 5. Even a cursory review of the results of all the survey questions that attempted to measure feelings of exclusion and alienation showed high levels across the board, boding negatively for online classes as a whole.

Figure 4: Video On and using Standard English trial; participants’ feeling of alienation

 

Figure 5: Video Off and using Standard English trial; participants’ feeling of alienation

 

And perhaps the most important result came from comparing the interaction factors of video and slang in the comprehension question. What our study found was that while there is a statistically meaningful difference in individual comprehension in response to both factors, i.e., video and slang, there was not significant interaction between them when it came to self-reported levels of comprehension. That is to say, contrary to our initial hypothesis, a factor like having video on doesn’t necessarily interact meaningfully with the differences caused by slang usage in comprehension.

Figure 6: The rate of participants correctly answering the quiz questions

 

However, when it comes to the actual analysis of the answers to the quiz questions, not just self-reported comprehension, there is a noticeable interaction factor. Figure 6 shows that when slang is used, the presence of video had a significant impact on actual comprehension as measured through the quizzes, whereas video had less impact when standard English was used. 

There are, of course, various factors that could be complicating this kind of analysis. The subjects chosen for the mock lesson, were it more or less visual, may have more of an effect on how these two variables interact. The length of the lesson may have an impact on all these variables depending on how often it becomes relevant that video is used or not. This study is not necessarily definitive but poses some important questions on how all of these variables can be utilized by educators in aiding comprehension and limiting alienation in classrooms.

Conclusion: The Classroom and Beyond

All in all, more research should be done with regards to the virtual learning environments that most of the world was thrown into due to the pandemic. There may be many key improvements to education in general, whether online classes are here to stay for a while or not. From our initial hypothesis that English slang negatively impacts international students’ engagement with and understanding of classroom material, we find that comprehension may be hindered by slang usage and a lack of visual cues, independently; however, international students seem to feel like they do not “fit in” with the class regardless of these variables, and their aptitude does not seem to suffer because of that in general.

We live in an ever growing technologically dependent society, yet online meetings can often feel like an obstacle and/or a divider when compared to in-person classes. In the article “Depression and Everyday Social Activity, Belonging, and Well-Being,” Michael and Todd stated that “When people experience positive social interactions, they should be more likely to feel a sense of belonging.” Alongside virtual meetings in the workplace, there is a lot that can be done by the hosts to improve distracting and frustrating video calls. Based on this small study, we recommend professors and teachers to encourage students to turn on their videos, with the caveat that there may be personal and privacy challenges. We can say that there may be evidence that doing so will help students’ comprehension of the material. We also suggest addressing slang and jargon when it arises in the classroom, making sure to at least clarify rather than exacerbate what may negatively impact some students’ learning outcome.

There are an endless number of questions to be asked in the realm of education research, with regards to both online and in-person mediums. Perhaps this experiment may be repeated with a live virtual classroom setting to really capture engagement and chat-box interaction data. Furthermore, there is something to be examined in asynchronous learning, i.e., these pre-recorded lectures in the study that subjects independently and asynchronously watched. In a pandemic that generates so many struggles, personally and in education, there is the possibility that Zoom lectures are a breakthrough to education access the world needs; we just need to optimize and adapt to it, rather than conceding at its shortcomings.

 

Further info

The PowerPoint form of this blog entry

A TedTalk which talks about the relationship between inclusiveness and your manner of speech

 

 

References

Albalawi, A.S. (2014). Saudi L2 learners’ knowledge and perceptions of academic English slang. [Order No. 1566835]. Southern Illinois University at Carbondale.

Bradford P.B. (2010). The acquisition of colloquial speech and slang in second language learners of English in El Paso, Texas . [Order No. 1484150]. The University of Texas at El Paso.

Steger, M. F., & Kashdan, T. B. (2009). Depression and Everyday Social Activity, Belonging, and Well-Being. Journal of counseling psychology, 56(2), 289–300. https://doi.org/10.1037/a0015416

Sueyoshi, A. & Hardison, D.M. (2005). The Role of Gestures and Facial Cues in Second Language Listening Comprehension. Language Learning, 55: 661-699. https://doi.org/10.1111/j.0023-8333.2005.00320.x

Zeki, C. P. (2009). The importance of non-verbal communication in classroom management. Procedia-Social and Behavioral Sciences, 1(1), 1443-1449.

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