In:
International Journal of Knowledge Discovery in Bioinformatics, IGI Global, Vol. 8, No. 2 ( 2018-07), p. 1-17
Kurzfassung:
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.
Materialart:
Online-Ressource
ISSN:
1947-9115
,
1947-9123
DOI:
10.4018/IJKDB.20180701
DOI:
10.4018/IJKDB.2018070101
Sprache:
Englisch
Verlag:
IGI Global
Publikationsdatum:
2018
ZDB Id:
2703506-2
