Investigating Gender Euphoria and Dysphoria on TikTok: Characterization and Comparison

TL;DR

This study investigates how transgender and nonbinary communities discuss gender dysphoria and gender euphoria on TikTok, using a multi-method text-analytic approach. By collecting 116 #gendereuphoria and 110 #genderdysphoria videos (with 1 description and 100 comments per video) and applying word clouds, semantic network analysis, Spearman rank-order correlation across top-$k$ words ($k$ varying in $[5,100]$), Vader sentiment analysis, and Latent Dirichlet Allocation, it reveals distinct linguistic patterns: descriptions show broad similarity across hashtags, while comments exhibit more differentiated language and sentiment, with gender euphoria receiving more positive engagement. The findings suggest that gender euphoria is described in more uniform terms across transfeminine and transmasculine experiences, whereas gender dysphoria is more differentiated by gender trajectory; comments tend to be more positive and may reflect supportive dynamics, while transcripts indicate potential dominance of transmasculine voices in certain spaces. Together, these results provide a methodological framework for analyzing transgender discourse on platformed spaces and offer insights into online knowledge exchange, community formation, and potential areas for further study on support and affirmation dynamics.

Abstract

With the emergence of short video-sharing platforms, engagement with social media sites devoted to opinion and knowledge dissemination has rapidly increased. Among these platforms, TikTok is one of the most popular globally and has become the platform of choice for transgender and nonbinary individuals, who have formed a large community to mobilize personal experience and exchange information. The knowledge produced in online spaces can influence the ways in which people understand and experience their own gender and transitions, as they hear about others and weigh experiential and medical knowledge against their own. This paper extends current research and past interview methods on gender euphoria and gender dysphoria to analyze what and how online communities on TikTok discuss these two types of gender experiences. Our findings indicate that gender euphoria and gender dysphoria are differently described in online TikTok spaces. These findings indicate similarities in the words used to describe gender dysphoria as well as gender euphoria in both the comments of videos and content creators' hashtags. Finally, our results show that gender euphoria is described in more similar terms between transfeminine and transmasculine experiences than gender dysphoria, which appears to be more differentiated by gendering experience and transition goals. We hope this paper can provide insights for future research on understanding transgender and nonbinary individuals in online communities.

Figures (8)

• Figure 1: An example of a TikTok video.
• Figure 2: Word cloud of comments for different hashtags.
• Figure 3: Spearman’s correlation between the top words of comments for different hashtags, by changing the $k$.
• Figure 4: Semantic Network Analysis for word-pairs in comments of different hashtags.
• Figure 5: Word cloud of video descriptions for the gender euphoria and gender dysphoria hashtags.