The establishment and evaluation of the automatic crisis balance analysis model for social network users based on artificial intelligence technology.

Shengxin Hu, Qing Wang,Lu Chen, Xingxin Zhang, Leiqing Huang,Tianyu He,Songhe Li, Xiangmin Dong,Bingxiang Yang

ISAIMS(2021)

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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.
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