Antoinette Woodson, Sydney Hesel, Paolo Barrientos, Amar Ebrahim, Nada Gad
Our research project functions to explore the different communication patterns and tendencies between males and females on social media. More specifically how these gender dynamics influence the communication styles. Our motivations for the research stem from our own personal experiences with gender stereotypes on social media. Additionally, we wanted to understand the potential sources of miscommunication between generations to further shed light on the different ways individuals express themselves on social media.
Existing studies have provided insight into how gender dynamics influence communication behavior. Differences in language use, emotional expression, and interaction frequency between genders have been shown to be factors influencing communication preference and understanding. To address these questions, the research team collected data from social media posts and comments made by Gen-Z individuals, both celebrities and non-celebrities, across different gender combinations. To further address these areas, our research group collected data from social media posts including comments, gender of commenters, and gender of posters for both celebrities and non-celebrities and across different gender combinations. We analyzed language choice, emoji usage, and patterns in interactions to identify common trends and tendencies within online communication.
Our results revealed definite communication patterns among gendered groups. Females were more likely to use affectionate/emotionally expressive language and frequently compliment physical appearance or express admiration. Males were commonly more rational and material in their communication style as they focused on achievements and tangible qualities. The red heart and fire emojis were the most commonly used among all groups in the study.
Introduction
This project researches differences in how people express themselves online depending on their gender, specifically through examining lexical variation on the social media platform Instagram. The population we are targeting are young adults, male and female ages 18-25, who are active users on the social media platform, Instagram. Our research will focus on studying the communication pattern differences between men and women on Instagram. Many sources and research findings show that men and women express themselves differently online, specifically in lexical variation. In online communication, lexical variation refers to word choice, emoticon use, hashtags, and phrases in interactions with people. We will observe the word choice and variation in expressions depending on the gender of the user, and also observe how it can change depending on what gender they are interacting with. We seek to analyze the differences in the context of comments on self-presentation posts through the comments on these posts, excluding business or advertisement posts. Our central focus is to study the relationship between gender and lexical variation on people’s Instagram. The goal of this study is to determine the difference in how males and females interact and express themselves online.
Background
The target population of the research belongs to the older segment of Generation Z. People belonging to this generation grew up with the internet, constantly communicating through consuming and creating digital media. Research indicates that Gen Zs are more comfortable using technology to communicate, even over face-to-face communication (Bredbenner, 2020). The most commonly used form of communication for this generation is through social media, which influences social norms between the genders. (Ridgeway, 1999). Our research looks at the relationship between gender and language variation, specifically on social media. Literature exploring the language variations in Instagram captions suggests that women were more likely to use polite phrases while men used more assertive language (Sari et al, 2020). The lexical variation between men and women suggests that women use more pronounced, emotional and expressive terms, kinship terms, and hesitation words, while men use more swear and taboo words, and friendship terms (Bamman, 2012). The differences between how men and women communicate online can even be seen through their use of emoticons, with women using emoticons to express feeling and support, while men used them primarily for teasing and sarcasm when in their own gender groups (Wolf, 2004). When both genders were interacting with each other in the same group, the men adopted the female standard of expressing more emoticons (Wolf, 2004). Furthermore, gender differences in lexical variation, more specifically in hashtag selection are mainly in part due to women’s higher levels of self-expression and more emotional interpersonal communication (Ye et al., 2017). Contrarily, men are more oriented toward goals and more inclined to share rational and objective information (Ye et al., 2017).
Methods
In approaching the study we first identified the most efficient way to collect data without skewing the results, while also collecting as much data as possible in order to decrease the likelihood of the results being distorted by a small sample size. To do so, we tasked each member working on the study to find a set of 20 posts from a pool of Gen-Z male and female celebrities, and Gen-Z male and female colleagues/friends. After each member found the posts, they were then tasked with identifying the top 5 comments and the gender of the user posting said comment, totaling to 500 data points. Those data points were then entered into a document, which allowed for the facilitation of isolating groups by gender of the poster and the commenter. With the data now isolated, the team identified patterns that could be used to prompt Chat-GPT-4 to search through the data. The data was then inserted into the model which calculated the quantities of the common keywords and emojis. The organized data provided allowed for convenient and efficient analysis based on the number of tendencies within each demographic. We double-checked 10% of the data to ensure accuracy in counting, and to ensure misspellings or slang versions of words were accounted for.
Results
After completing our data collection and graph, we found that both genders commented more on posts made by their same gender. We also found that females commented the most out of all the user groups with 44% of the data being women commenting the most on other posts done by women. The graph shows the total number of male-on-male comments was 168 with 110 emojis used. The female-on-female comments had a total of 220 and 176 emojis were used. We can see that females use more emojis than males, but males spread their emojis out more throughout comments, whereas women typically stack their emojis more in one comment. The male-on-female comments showed much less interaction with only 38 comments in total but 54 emojis were used. Lastly, the female on male also contained much less engagement with 71 comments and 53 emojis used. The results show that females still engage and interact more with both males and females in online comments on Instagram. We also looked at the top three emojis used by males and females. The most commonly used emojis by females were the heart eyes, heart, and fire emoji, and the male’s most common emojis were heart, laughing, and fire emoji when commenting on males, and heart eyes, heart, and fire emoji when commenting on females. Males tended to adopt the heart-eyes emoji when talking to females.
One of the main subjects we decided to observe and quantify in the data was word choice, and in what contexts words were used most frequently. When females commented on other female’s posts, the most commonly used words were emotional compliments. For example, words expressing feelings of admiration and compliments, such as “beautiful,” “pretty,” “gorgeous,” “stunning,” and, “cute”, appeared in 33% of comments. Additionally, “love” and “lovely” appeared in 22% of comments. The use of “love” only appeared 5 other times in another category, females commenting on male posts. When females commented on male posts, their compliments began to exclude words such as “beautiful,” “pretty,” “gorgeous,” and “stunning,” and were more likely to use “cute” as an emotional compliment. While we cannot prove the cause of why this would happen, we can infer that the level of emotional expression is being limited. Other commonly used words were “ate,” “best,” and “serving,” all of which lean towards a more material expression of admiration, used to express that someone is stylish or confident. Additionally, a tendency that stood out among female commenters was their tendency to add letters onto words. We infer that this is done to add emphasis, for example, “Elllie_rose” comments ”the cat pic you are kiddinggggggg” on a post by user “Rubylyn”, having the same effect as drawn-out words in verbal dialogue. This was done in 8% of all comments made by female users, and only 2% by male users.
When males commented on other males’ posts, they used adjectives that were less emotional, being more material, and more rational. For example, some of their top used words were “fit” and “fitted”, which express praise for the poster’s outfit, which is inherently material.
Additionally, words such as “winning” and “mid”, a slang term expressing mediocracy, exemplify compliments utilizing rational words, rather than emotional words. These comments are still supportive, however lean towards observations suggesting achievement rather than forward admiration. However, this changed when males commented on female’s posts, with their top words changing to “gorgeous,” “cute,” and, “queen”. These words were not used at all on other males’ posts, so male users are more overtly changing their lexical choices when commenting on female posts. This is a contrast to the female commentators, who seem to have dialed back their compliments but did not change their word choice as overtly.
Discussion
Our findings indicate some lexical variation dependent on gender on social media. Females utilize a more expressive and emotional communication style, especially when engaging with other females. Their comments consist of affectionate compliments that boost confidence. This behavior shows the supportive nature of female interactions on digital platforms. Their style changes slightly when commenting on male posts, dialing back the emotional strength of the compliments. Additionally, the language and emojis used by women tend to amplify the emotional intensity of their interaction. Males tend to imply that something is cool or impressive, using more material terms. However, when interacting with women’s posts, men use more affectionate communication. Our findings could be interpreted to reveal how current gender norms and stereotypes influence digital communication. Males’ interactions often center around achievements, while females’ interactions are rich in compliments. Despite our findings, we find it difficult to make concrete conclusions given the limited size of our data. The data could have been skewed by unknown factors, thus any concrete conclusions from this data require further studies of Gen-Z’s tendencies within comment sections on Instagram. Our research into
Instagram comments adds to the understanding of how males and females communicate online, and what changes occur during cross-gender interactions. That being said, we hope our findings and study are able to set the stage for future research to help understand gender norms.
References
Bamman, D., Eisenstein, J., & Schnoebelen, T. (2012). Gender identity and lexical variation in social media. Journal of Sociolinguistics, 18(2), 135–160. https://doi.org/10.1111/josl.12080
Bredbenner, Jamie, and Lisa M. Parcell. “Generation Z: A Study of Its Workplace
Communication Behaviors and Future Preferences.” Generation z: A Study of Its Workplace Communication Behaviors and Future Preferences, Wichita State University, 2020.
Ridgeway, C. L., & Smith-Lovin, L. (1999). The gender system and interaction. Annual Review of Sociology, 25(1), 191–216. https://doi.org/10.1146/annurev.soc.25.1.191
Sari, I. P., Gunawan, W., & Sudana, D. (2020). Language variations in Instagram captions.
Proceedings of the 4th International Conference on Language, Literature, Culture, and Education (ICOLLITE 2020). https://doi.org/10.2991/assehr.k.201215.053
Wolf, A. (2004). Emotional expression online: Gender differences in emoticon use. CyberPsychology & Behavior, 3(5), 827–833. https://doi.org/10.1089/10949310050191809
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