The Shifting Tides of Sentiment: A 5-Year Analysis of Gender Affirming Surgery Discourse on Social Media
Cole Holan, Arman Fijany, Jorys Martinez-Jorge

TL;DR
This study analyzed social media posts about transgender care from 2018 to 2023 and found a significant increase in negative sentiment over time.
Contribution
This is the first large-scale NLP analysis of sentiment trends in online discourse about transgender healthcare.
Findings
Annual social media post volume about gender surgery increased 20-fold from 2018 to 2023.
78% of posts were classified as negative, with transgender-specific topics showing significantly more negativity than general gender-affirming surgery posts.
Sentiment analysis revealed a consistent shift toward more negative and less positive attitudes over the study period.
Abstract
This study aims to examine the sentiment and polarization of social media content regarding transgender care. We seek to quantitatively analyze social media posts related to transgender care using sentiment analysis, assessing the extent of positive or negative bias in online discussions about transgender healthcare. By establishing a baseline understanding of how online misinformation may impact public perceptions of transgender care, we highlight the importance of addressing online extremism in healthcare as a public health concern. This research represents the first large-scale natural language processing (NLP) analysis of online sentiment towards transgender care, utilizing sentiment analysis to minimize bias and provide quantitative insights into the impact of online rhetoric on public perception and patient care. The lead author mined X for posts that mentioned transgender…
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Taxonomy
TopicsSocial Media in Health Education
