Analysis of emotional characteristics of Weibo "tree hole" users with different suicide risk

Tianyu He, Yuyu Zheng, Jing Bai, Pan Chen, Yue Ma, Guanghui Fu, Shengxin Hu, Songhe Li, Zhisheng Huang, Qian Liu, Bing Xiang Yang

Abstract: Background Suicide is a global public health and mental health problem. With the rapid development of internet technology, more and more people tend to express their suicidal tendencies and suicidal intentions online. The difference of emotional characteristics between high and low risk of suicide messages should be analyzed to help identify suicide risk and provide early intervention. Methods The "tree hole" intelligent robot captures message data, then randomly selects the same number of high and low suicide risk messages manually, and the high frequency keywords of high and low suicide risk messages are obtained by word segmentation and a TF-IDF algorithm. The keywords are analyzed by Gephi software, and the emotion dictionary provided by Boson is used to judge the emotional tendency of high and low suicide risk users. Results The emotional score of high suicide risk messages was -3.511 ~ 2.514, averaging (-0.225±0.405), while the total score of low suicide risk messages was -4.547 ~ 3.403, averaging (-0.121±0.628). Low suicide risk messages mainly focused on negative emotions, interpersonal relationships and social support, while high suicide risk messages mainly centered on invited suicide, means, locations and time of suicide. Conclusion There are differences in emotional characteristics between high and low suicide risk messages. The higher the suicide risk, the more obvious the negative tendency of the users' emotions. More attention is needed to the greater potential for suicide among this group of users and psychological support and interventions should be included.