Waseda University, Waseda Institute of Political Economy, Japan.
University of Michigan, Department of Political Science, United States.
Soc Sci Med. 2020 May;253:112960. doi: 10.1016/j.socscimed.2020.112960. Epub 2020 Mar 24.
Social media data is increasingly used to gain insights into trends in mental health, but prior studies aimed at confirming a link between online expression of suicidal ideation on social media and actual suicide deaths have been inconclusive. Using comprehensive six-year data sets of Twitter posts and suicide deaths in Japan, we examine the diurnal relationship between the proportional incidence of a suicide-related keyword, "kietai" ("I want to disappear"), and suicide deaths with an OLS regression model. We also use co-occurrence analysis to reveal changes in the linguistic context of the suicide-related keyword at different hours of the day. We find a clear diurnal pattern in the use of this suicide-related keyword, peaking between 1am and 5am. This diurnal trend is positively correlated with suicide deaths among younger cohorts (ages 15 to 44), but the correlation is negative among older adults (45 and over). The correlation among young adults strengthens when a delay between tweet incidence and suicide deaths is included. Compared to daytime tweets, nighttime tweets exhibited a stronger relationship between words related to self-disgust and words directly indicating suicidal intent. This study confirms the hypothesised link between online suicidal ideation and suicide death. Despite frequent flippant use of the keyword, the consistent correlation and the diurnal changes in the context of the keyword's usage demonstrate the value of social media data to the study of mental health trends in groups at risk of suicide.
社交媒体数据越来越多地被用于深入了解心理健康趋势，但之前旨在确认社交媒体上表达自杀意念与实际自杀死亡之间联系的研究尚无定论。本研究使用日本全面的六年 Twitter 帖子和自杀死亡数据集，使用 OLS 回归模型检验与自杀相关的关键词“kietai”（“我想消失”）的比例发病率与自杀死亡之间的昼夜关系。我们还使用共现分析来揭示该自杀相关关键词在一天不同时间的语言环境中的变化。我们发现，该自杀相关关键词的使用存在明显的昼夜模式，峰值出现在凌晨 1 点至 5 点之间。这种昼夜趋势与年轻人群（15 至 44 岁）的自杀死亡呈正相关，但在老年人（45 岁及以上）中呈负相关。当包含推文发病和自杀死亡之间的延迟时，年轻成年人之间的相关性增强。与白天的推文相比，夜间的推文显示出与自我厌恶相关的词与直接表示自杀意图的词之间的关系更强。本研究证实了在线自杀意念与自杀死亡之间的假设联系。尽管该关键词经常被轻率地使用，但关键词使用背景的一致性关联和昼夜变化证明了社交媒体数据对于研究有自杀风险的群体的心理健康趋势具有价值。
