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.
Highlights
Suicide is a leading cause of death worldwide
Several studies investigated associations between suicide and consumer behaviors related to the public mood. [11,12,13] Studies on alcohol consumption and suicide suggest that population drinking tends to promote completed suicide. [13,14,15] A recent study in Taiwan found a correlation between suicide and lottery sales that was interpreted as reflecting hopelessness at the social level
At 31 per 100,000, the annual suicide rate in South Korea is highest among the 30 Organization for Economic Cooperation and Development (OECD) countries as of 2009. [24,25] In addition, South Korea is a global leader in internet infrastructure and usage
Summary
Suicide is a leading cause of death worldwide. According to the World Health Organization, in the year 2020 approximately 1.53 million people will die from suicide. [1] As Durkheim established, suicide is not a mere individual phenomenon, but it is influenced by social and environmental factors. [2] These include economic indicators, social cohesion, publicized celebrity suicides, sunlight duration and temperature. [3,4,5,6,7,8,9,10] these studies found meaningful results, few of them examined the public mood state.Recently, several studies investigated associations between suicide and consumer behaviors related to the public mood. [11,12,13] Studies on alcohol consumption and suicide suggest that population drinking tends to promote completed suicide. [13,14,15] A recent study in Taiwan found a correlation between suicide and lottery sales that was interpreted as reflecting hopelessness at the social level. [11] these consumer behaviors are at best indirect indicators of public mood.Social media data such as weblog contents are more promising sources to gauge the public mood. [16,17,18] Despite the diversity of content at an individual level, the aggregate of millions of social media data points may provide a pragmatic representation of public mood. [18] Previous studies suggested new methods to measure national happiness by tracking the usage of key words among users of social media services. [19,20] it has been shown that online social media data can be used to predict changes in the stock market, [18] influenza infection rates, [21,22] and box office receipts. [23] social media data could be a promising source for investigating the association between suicide and public mood and for the refinement of suicide prediction models.At 31 per 100,000, the annual suicide rate in South Korea is highest among the 30 Organization for Economic Cooperation and Development (OECD) countries as of 2009. [24,25] In addition, South Korea is a global leader in internet infrastructure and usage. [26] These conditions enabled us to investigate suicide and social media data. Several studies investigated associations between suicide and consumer behaviors related to the public mood. [11] these consumer behaviors are at best indirect indicators of public mood Social media data such as weblog contents are more promising sources to gauge the public mood. [23] social media data could be a promising source for investigating the association between suicide and public mood and for the refinement of suicide prediction models. As described in Methods, we extracted two candidate variables from a very large body of social media postings These two variables focused on the topics of suicide and dysphoria in the form of frequency among weblog entries
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