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The establishment and evaluation of the automatic crisis balance analysis model for social network users based on artificial intelligence technology
Hu Shengxin (Wuhan University), Qing Wang (Wuhan University), Lu Chen (Wuhan University), Zhang Xingxin (Wuhan University), Huang Leiqing (Wuhan University), He Tianyu (Wuhan University), Songhe Li (Wuhan University), Xiangmin Dong (Beijing University of Technology), Yang Bingxiang (Wuhan University)
Abstract: Online social media provides people with a platform to express their emotions anonymously. Social media has been identified as an important data source for suicide prevention related to emotional problems in China. Almost Three million messages were published by 450,000 users in a particular Chinese social media data base. This study aims to develop a Crisis Balance Analysis Model based on concepts of "balancing factors" as described by Aguilera. Through interactions with psychological experts, deep learning architecture that was built and refined. Three annotation levels free annotations (zero cost), easy annotations (by psychology students), and hard annotations (by psychology experts) were used. Our Model was evaluated accordingly and showed that its performance at each level was promising. Finally, suicide risks, cognitive distortions and interpersonal problems could be identified for messages from social media users using this model, which providing basis for proactive crisis intervention.