» Articles » PMID: 23630615

Predicting National Suicide Numbers with Social Media Data

Overview
Journal PLoS One
Date 2013 May 1
PMID 23630615
Citations 34
Authors
Affiliations
Soon will be listed here.
Abstract

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors - consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

Citing Articles

Predicting state level suicide fatalities in the united states with realtime data and machine learning.

Patel D, Sumner S, Bowen D, Zwald M, Yard E, Wang J Npj Ment Health Res. 2024; 3(1):3.

PMID: 38609512 PMC: 10956008. DOI: 10.1038/s44184-023-00045-8.


National Trends in Suicides and Male Twin Live Births in the US, 2003 to 2019: An Updated Test of Collective Optimism and Selection in Utero.

Singh P, Gailey S, Das A, Bruckner T Twin Res Hum Genet. 2023; :1-8.

PMID: 38099411 PMC: 11178679. DOI: 10.1017/thg.2023.49.


Dynamic reciprocal relationships between traditional media reports, social media postings, and youth suicide in Taiwan between 2012 and 2021.

Chen Y, Chen F, Wu K, Lu T, Chi Y, Yip P SSM Popul Health. 2023; 24:101543.

PMID: 37965108 PMC: 10641279. DOI: 10.1016/j.ssmph.2023.101543.


Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health.

Oudin A, Maatoug R, Bourla A, Ferreri F, Bonnot O, Millet B J Med Internet Res. 2023; 25:e44502.

PMID: 37792430 PMC: 10585447. DOI: 10.2196/44502.


Development of a Machine Learning Model to Estimate US Firearm Homicides in Near Real Time.

Swedo E, Alic A, Law R, Sumner S, Chen M, Zwald M JAMA Netw Open. 2023; 6(3):e233413.

PMID: 36930150 PMC: 10024196. DOI: 10.1001/jamanetworkopen.2023.3413.


References
1.
Lester D, Yang B . The relationship between divorce, unemployment and female participation in the labour force and suicide rates in Australia and America. Aust N Z J Psychiatry. 1991; 25(4):519-23. DOI: 10.3109/00048679109064445. View

2.
Mercy J, Kresnow M, OCarroll P, Lee R, Powell K, Potter L . Is suicide contagious? A study of the relation between exposure to the suicidal behavior of others and nearly lethal suicide attempts. Am J Epidemiol. 2001; 154(2):120-7. DOI: 10.1093/aje/154.2.120. View

3.
Bertolote J, Fleischmann A . Suicidal behavior prevention: WHO perspectives on research. Am J Med Genet C Semin Med Genet. 2005; 133C(1):8-12. DOI: 10.1002/ajmg.c.30041. View

4.
Sudak H, Sudak D . The media and suicide. Acad Psychiatry. 2006; 29(5):495-9. DOI: 10.1176/appi.ap.29.5.495. View

5.
Sisask M, Varnik A . Media roles in suicide prevention: a systematic review. Int J Environ Res Public Health. 2012; 9(1):123-38. PMC: 3315075. DOI: 10.3390/ijerph9010123. View