title: Tracking suicide risk factors through Twitter in the US.
abstract: BACKGROUND
  Suicide is a leading cause of death in the United States. Social media such as Twitter is an emerging surveillance tool that may assist researchers in tracking suicide risk factors in real time.
  
  
  OBJECTIVE
  To identify suicide-related risk factors through Twitter conversations by matching on geographic suicide rates from vital statistics data.
  
  
  METHODS
  At-risk tweets were filtered from the Twitter stream using keywords and phrases created from suicide risk factors. Tweets were grouped by state and departures from expectation were calculated. The values for suicide tweeters were compared against national data of actual suicide rates from the Centers for Disease Control and Prevention.
  
  
  RESULTS
  A total of 1,659,274 tweets were analyzed over a 3-month period with 37,717 identified as at-risk for suicide. Midwestern and western states had a higher proportion of suicide-related tweeters than expected, while the reverse was true for southern and eastern states. A strong correlation was observed between state Twitter-derived data and actual state age-adjusted suicide data.
  
  
  CONCLUSIONS
  Twitter may be a viable tool for real-time monitoring of suicide risk factors on a large scale. This study demonstrates that individuals who are at risk for suicide may be detected through social media.
authors.affiliation: <location>Department of Health Science, Brigham Young University, Provo, UT, USA</location>
authors.forename: Jared
authors.initials: J
authors.lastname: Jashinsky
authors.affiliation: <location>Department of Computer Science and Electrical Engineering, Brigham Young University Idaho, Rexburg, ID, USA</location>
authors.forename: Scott H
authors.initials: SH
authors.lastname: Burton
authors.affiliation: <location>Department of Health Science, Brigham Young University, Provo, UT, USA</location>
authors.forename: Carl L
authors.initials: CL
authors.lastname: Hanson
authors.affiliation: <location>Department of Health Science, Brigham Young University, Provo, UT, USA</location>
authors.forename: Josh
authors.initials: J
authors.lastname: West
authors.affiliation: <location>Department of Computer Science, Brigham Young University, Provo, UT, USA</location>
authors.forename: Christophe
authors.initials: C
authors.lastname: Giraud-Carrier
authors.affiliation: <location>Department of Health Science, Brigham Young University, Provo, UT, USA</location>
authors.forename: Michael D
authors.initials: MD
authors.lastname: Barnes
authors.affiliation: <location>Department of Health Science, Brigham Young University, Provo, UT, USA</location>
authors.forename: Trenton
authors.initials: T
authors.lastname: Argyle
mesh_terms: D006801:Humans; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D061108:Social Media; D013405:Suicide / Q000706:statistics & numerical data*; D014481:United States / Q000453:epidemiology; D000092864:Suicide Prevention
keywords: Twitter; social media; suicide