Assessing mental health signals among sexual and gender minorities using Twitter data

Sexual and gender minorities face extreme challenges that breed stigma with alarming consequences damaging their mental health. Nevertheless, sexual and gender minority people and their mental health needs remain little understood. Because of stigma, sexual and gender minorities are often unwilling to self-identify themselves as sexual and gender minorities when asked. However, social media have become popular platforms for health-related researches. We first explored methods to find sexual and gender minorities through their self-identifying tweets, and further classified them into 11 sexual and gender minority subgroups. We then analyzed mental health signals extracted from these sexual and gender minorities’ Twitter timelines using a lexicon-based analysis method. We found that (1) sexual and gender minorities expressed more negative feelings, (2) the difference between sexual and gender minority and non-sexual and gender minority people is shrinking after 2015, (3) there are differences among sexual and gender minorities lived in different geographic regions, (4) sexual and gender minorities lived in states with sexual and gender minority-related protection laws and policies expressed more positive emotions, and (5) sexual and gender minorities expressed different levels of mental health signals across different sexual and gender minority subgroups.