Characteristics of High Suicide Risk Messages From Users of a Social Network-Sina Weibo Tree Hole

BackgroundPeople with suicidal ideation post suicide-related information on social media, and some may choose collective suicide. Sina Weibo is one of the most popular social media platforms in China, and Zoufan is one of the largest depression Tree Holes. To collect suicide warning information and prevent suicide behaviors, researchers conducted real-time network monitoring of messages in the Zoufan tree hole via artificial intelligence robots. ObjectiveTo explore characteristics of time, content and suicidal behaviors by analyzing high suicide risk comments in the Zoufan tree hole. MethodsKnowledge graph technology was used to screen high suicide risk comments in the Zoufan tree hole. Users' level of activity was analyzed by calculating the number of messages per hour. Words in messages were segmented by a Jieba tool. Keywords and a keywords co-occurrence matrix were extracted using a TF-IDF algorithm. Gephi software was used to conduct keywords co-occurrence network analysis. ResultsAmong 5,766 high suicide risk comments, 73.27% were level 7 (suicide method was determined but not the suicide date). Females and users from economically developed cities are more likely to express suicide ideation on social media. High suicide risk users were more active during nighttime, and they expressed strong negative emotions and willingness to end their life. Jumping off buildings, wrist slashing, burning charcoal, hanging and sleeping pills were the most frequently mentioned suicide methods. About 17.55% of comments included suicide invitations. Negative cognition and emotions are the most common suicide reason. ConclusionUsers sending high risk suicide messages on social media expressed strong suicidal ideation. Females and users from economically developed cities were more likely to leave high suicide risk comments on social media. Nighttime was the most active period for users. Characteristics of high suicide risk messages help to improve the automatic suicide monitoring system. More advanced technologies are needed to perform critical analysis to obtain accurate characteristics of the users and messages on social media. It is necessary to improve the 24-h crisis warning and intervention system for social media and create a good online social environment.

Automated summary

This study explored the characteristics of high suicide risk comments on social media, including the time, content, and suicidal behaviors of users. The results revealed that females and users from economically developed cities were more likely to express suicidal ideation on social media. Additionally, nighttime was found to be the most active period for users.