title: Twitter: A Novel Tool for Studying the Health and Social Needs of Transgender Communities.
abstract: BACKGROUND
  Limited research has examined the health and social needs of transgender and gender nonconforming populations. Due to high levels of stigma, transgender individuals may avoid disclosing their identities to researchers, hindering this type of work. Further, researchers have traditionally relied on clinic-based sampling methods, which may mask the true heterogeneity of transgender and gender nonconforming communities. Online social networking websites present a novel platform for studying this diverse, difficult-to-reach population.
  
  
  OBJECTIVE
  The objective of this study was to attempt to examine the perceived health and social needs of transgender and gender nonconforming communities by examining messages posted to the popular microblogging platform, Twitter.
  
  
  METHODS
  Tweets were collected from 13 transgender-related hashtags on July 11, 2014. They were read and coded according to general themes addressed, and a content analysis was performed. Qualitative and descriptive statistics are presented.
  
  
  RESULTS
  There were 1135 tweets that were collected in total. Both "positive" and "negative" events were discussed, in both personal and social contexts. Violence, discrimination, suicide, and sexual risk behavior were discussed. There were 34.36% (390/1135) of tweets that addressed transgender-relevant current events, and 60.79% (690/1135) provided a link to a relevant news article or resource.
  
  
  CONCLUSIONS
  This study found that transgender individuals and allies use Twitter to discuss health and social needs relevant to the population. Real-time social media sites like Twitter can be used to study issues relevant to transgender communities.
authors.affiliation: Department of Community Health Sciences, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Evan A
authors.initials: EA
authors.lastname: Krueger
authors.affiliation: UC Institute for Prediction Technology, Department of Family Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
authors.forename: Sean D
authors.initials: SD
authors.lastname: Young