Crisis · 2013 · 367 citations · 22 references
Public HealthPublic Health InformaticsPublic Health SurveillanceSocial Media AnalyticsSuicide PreventionEvent DetectionSocial MediaSocial Media SurveillanceSuicide Risk AssessmentPredictors Of Suicide RiskReal-time MonitoringSuicide EpidemiologySuicide MortalitySuicide Risk DetectionSuicide Surveillance Systems
Suicide is a leading cause of death in the United States, and social media such as Twitter is an emerging surveillance tool that may enable real‑time tracking of suicide risk factors. The study aims to identify suicide‑related risk factors by analyzing Twitter conversations and matching them to geographic suicide rates from vital.
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.To identify suicide-related risk factors through Twitter conversations by matching on geographic suicide rates from vital statistics data.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.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.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.
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The Measurement of Observer Agreement for Categorical Data
J. Richard Landis, Gary G. Koch · Biometrics · 1977 · 78.9K citations · Full text
Predicting the Future with Social Media
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