The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
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. Aims: To identify suicide-related risk factors through Twitter conversations by matching on geographic suicide rates from vital statistics data. Method: 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. Conclusion: 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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BackgroundPredicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”
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Cited by
Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning
Mohr, D. C., Zhang, M., & Schueller, S. M. (2017) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032816-044949 · Cited by 802
Higher temperatures increase suicide rates in the United States and Mexico
Burke, M., González, F., Baylis, P., Heft-Neal, S., Baysan, C., Basu, S., & Hsiang, S. (2018) · Nature Climate Change · doi:10.1038/s41558-018-0222-x · Cited by 604
Social media and suicide prevention: a systematic review
Robinson, J., Cox, G., Bailey, E., Hetrick, S., Rodrigues, M., Fisher, S., & Herrman, H. (2016) · Early Intervention in Psychiatry · doi:10.1111/eip.12229 · Cited by 336
Depression and Self-Harm Risk Assessment in Online Forums
Yates, A., Cohan, A., & Goharian, N. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d17-1322 · Cited by 323
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications
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Metadata
- Authors
- Jashinsky, J., Burton, S. H., Hanson, C. L., West, J., Giraud-Carrier, C., Barnes, M. D., & Argyle, T.
- Venue
- Crisis
- Publisher
- Hogrefe Publishing Group
- Published
- 2014-01-01
- Volume
- 35
- Issue
- 1
- Pages
- 51-59
- ISSN
- 0227-5910 (ISSN-L)
- 2151-2396
- OpenAlex
- W2003834798
- Cited by
- 342
- References
- 28
- FWCI
- 26.11
- Type
- journal article
- Language
- en
- Open access
- closed
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