title: #WhyWeTweetMH: Understanding Why People Use Twitter to Discuss Mental Health Problems.
abstract: Use of the social media website Twitter is highly prevalent and has led to a plethora of Web-based social and health-related data available for use by researchers. As such, researchers are increasingly using data from social media to retrieve and analyze mental health-related content. However, there is limited evidence regarding why people use this emerging platform to discuss mental health problems in the first place.
  
  
  
  The aim of this study was to explore the reasons why individuals discuss mental health on the social media website Twitter. The study was the first of its kind to implement a study-specific hashtag for research; therefore, we also examined how feasible it was to circulate and analyze a study-specific hashtag for mental health research.
  
  
  
  Text mining methods using the Twitter Streaming Application Programming Interface (API) and Twitter Search API were used to collect and organize tweets from the hashtag #WhyWeTweetMH, circulated between September 2015 and November 2015. Tweets were analyzed thematically to understand the key reasons for discussing mental health using the Twitter platform.
  
  
  
  Four overarching themes were derived from the 132 tweets collected: (1) sense of community; (2) raising awareness and combatting stigma; (3) safe space for expression; and (4) coping and empowerment. In addition, 11 associated subthemes were also identified.
  
  
  
  The themes derived from the content of the tweets highlight the perceived therapeutic benefits of Twitter through the provision of support and information and the potential for self-management strategies. The ability to use Twitter to combat stigma and raise awareness of mental health problems indicates the societal benefits that can be facilitated via the platform. The number of tweets and themes identified demonstrates the feasibility of implementing study-specific hashtags to explore research questions in the field of mental health and can be used as a basis for other health-related research.
authors.affiliation: Health eResearch Centre, University of Manchester, Manchester, United Kingdom.|Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.
authors.forename: Natalie
authors.identifier: 0000-0001-7414-1541
authors.initials: N
authors.lastname: Berry
authors.affiliation: Spectrum Centre for Mental Health Research, School of Health and Medicine, Lancaster University, Lancaster, United Kingdom.
authors.forename: Fiona
authors.identifier: 0000-0001-6594-4350
authors.initials: F
authors.lastname: Lobban
authors.affiliation: School of Computer Science, University of Manchester, Manchester, United Kingdom.
authors.forename: Maksim
authors.identifier: 0000-0001-8574-5439
authors.initials: M
authors.lastname: Belousov
authors.affiliation: Centre for Biostatistics, Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.
authors.forename: Richard
authors.identifier: 0000-0002-1218-675X
authors.initials: R
authors.lastname: Emsley
authors.affiliation: Health eResearch Centre, University of Manchester, Manchester, United Kingdom.|School of Computer Science, University of Manchester, Manchester, United Kingdom.
authors.forename: Goran
authors.identifier: 0000-0003-0795-5363
authors.initials: G
authors.lastname: Nenadic
authors.affiliation: Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom.|Manchester Academic Health Science Centre, Greater Manchester Mental Health NHS Foundation Trust, Manchester, United Kingdom.
authors.forename: Sandra
authors.identifier: 0000-0002-6197-5333
authors.initials: S
authors.lastname: Bucci
mesh_terms: D006801:Humans; D020407:Internet; D001523:Mental Disorders / Q000175:diagnosis* / Q000517:prevention & control / Q000523:psychology*; D061108:Social Media
keywords: Twitter; mental health; social media