Characterizing transgender health issues in Twitter. Issue 1 (1st February 2019)

• Record Type: Journal Article
• Authors: Karami, Amir; Webb, Frank; Kitzie, Vanessa L.
• Is Part Of: Proceedings of the Association for Information Science and Technology. Volume 55:Issue 1(2018)
• Page Start: 207
• Page End: 215
• Publication Date: 2019-02-01
• Subjects: Transgender -- health -- topic modeling -- linguistics analysis -- Twitter; Information science -- Congresses; Information technology -- Congresses; Information science; Information technology; Conference papers and proceedings; 020
• DOI: 10.1002/pra2.2018.14505501023
• Languages: English
• ISSNs: 2373-9231

Abstract

ABSTRACT: Although there are millions of transgender people in the world, a lack of information exists about their health issues. This issue has consequences for the medical field, which only has a nascent understanding of how to identify and meet this population's health‐related needs. Social media sites like Twitter provide new opportunities for transgender people to overcome these barriers by sharing their personal health experiences. Our research employs a computational framework to collect tweets from self‐identified transgender users, detect those that are health‐related, and identify their information needs. This framework is significant because it provides a macro‐scale perspective on an issue that lacks investigation at national or demographic levels. Our findings identified 54 distinct health‐related topics that we grouped into 7 broader categories. Further, we found both linguistic and topical differences in the health‐related information shared by transgender men (TM) as compared to transgender women (TW). These findings can help inform medical and policy‐based strategies for health interventions within transgender communities. Also, our proposed approach can inform the development of computational strategies to identify the health‐related information needs of other marginalized populations.