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Suicide Risk on Twitter

Suicide Risk on Twitter

Samah Jamal Fodeh, Edwin D. Boudreaux, Rixin Wang, Dennis Silva, Robert Bossarte, Joseph Lucien Goulet, Cynthia Brandt, Hamada Hamid Altalib
Copyright: © 2018 |Volume: 8 |Issue: 2 |Pages: 17
ISSN: 1947-9115|EISSN: 1947-9123|EISBN13: 9781522544678|DOI: 10.4018/IJKDB.2018070101
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MLA

Fodeh, Samah Jamal, et al. "Suicide Risk on Twitter." IJKDB vol.8, no.2 2018: pp.1-17. http://doi.org/10.4018/IJKDB.2018070101

APA

Fodeh, S. J., Boudreaux, E. D., Wang, R., Silva, D., Bossarte, R., Goulet, J. L., Brandt, C., & Altalib, H. H. (2018). Suicide Risk on Twitter. International Journal of Knowledge Discovery in Bioinformatics (IJKDB), 8(2), 1-17. http://doi.org/10.4018/IJKDB.2018070101

Chicago

Fodeh, Samah Jamal, et al. "Suicide Risk on Twitter," International Journal of Knowledge Discovery in Bioinformatics (IJKDB) 8, no.2: 1-17. http://doi.org/10.4018/IJKDB.2018070101

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Abstract

While many studies have explored the use of social media and behavioral changes of individuals, few examined the utility of using social media for suicide detection and prevention. The study by Jashinsky et al. identified specific language patterns associated with a set of twelve suicide risk factors. The authors extended these methods to assess the significance of the language used on Twitter for suicide detection. This article quantifies the use of Twitter to express suicide related language, and its potential to detect users at high risk of suicide. The authors searched Twitter for tweets indicative of 12 suicide risk factors. This paper divided Twitter users into two groups: “high risk” and “at risk” based on two of the risk factors (“self-harm” and “prior suicide attempts”) and examined language patterns by computing co-occurrences of terms in tweets which helped identify relationships between suicide risk factors in both groups.

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