Mapping Gender Transition Sentiment Patterns via Social Media Data

Toward Decreasing Transgender Mental Health Disparities

Oliver Haimson
2 min readAug 19, 2019

This blog post summarizes a research paper that was published in Journal of the American Medical Informatics Association (JAMIA)’s special issue on “Health informatics and health equity: improving our reach and impact” in 2019.

Transgender people (including non-binary people) face substantial mental health disparities, and especially during the transition process, emotional well-being can change rapidly and unpredictably. Understanding an approximation of how people feel over time during gender transition — what I call mapping gender transition sentiment patterns — can help trans people by enabling them to prepare for, and put support in place for, particularly difficult time periods. Yet, tracking sentiment over time throughout gender transition is challenging using traditional research methods. In this study, I used social media data to measure and understand average gender transition sentiment patterns.

I analyzed text data from 240 Tumblr transition blogs (blogs where people document their gender transitions), and found that:

  1. Positive sentiment increases over time on average throughout gender transition, particularly when people receive supportive responses to trans identity disclosures.
  2. After trans identity disclosures to family members, people experienced temporary increased negative sentiment, followed by increased positive sentiment in the long term.
  3. After trans identity disclosures on Facebook, an important means of mass disclosure, those with supportive networks experienced increased positive sentiment.

Gender transition sentiment patterns found in this work, on average, are illustrated in this conceptual visualization:

Conceptual visualization of gender transition sentiment patterns over time on average. For more information, please see full paper.

These results have important implications for trans people, and mental healthcare providers who work with trans people. By knowing these patterns in advance, they can put support structures in place throughout the gender transition process. In this way, understanding gender transition sentiment patterns can help reduce the mental health disparities that trans people face.

It is important to understand average gender transition sentiment patterns, but equally important to consider that for individual people, wellbeing over time is complicated by intersecting identity facets and life transitions experienced at the same time as their gender transitions. I examined these complexities and intersections in a new paper that is currently under review.

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citation: Oliver L. Haimson. Mapping gender transition sentiment patterns via social media data: toward decreasing transgender mental health disparities. Journal of the American Medical Informatics Association, Volume 26, Issue 8–9, August/September 2019, Pages 749–758, https://doi.org/10.1093/jamia/ocz056

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Oliver Haimson

Assistant Professor @UMSI researching social computing, HCI, designing trans tech, identity transitions, content moderation, social media. he/him