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›› 2014, Vol. 31 ›› Issue (6): 814-820.DOI: 10.7523/j.issn.2095-6134.2014.06.013

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Depression and anxiety prediction on microblogs

BAI Shuotian1, HAO Bibo1, LI Ang1, NIE Dong1, ZHU Tingshao2   

  1. 1. School of Computer and Control Engineer, University of Chinese Academy of Sciences, Beijing 100049, China;
    2. Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2013-11-06 Revised:2014-02-24 Online:2014-11-15
  • Supported by:

    Supported by NSFC(61070115),Strategic Priority Research Program(XDA06030800) and 100-Talent Project(Y2CX093006) from CAS

Abstract:

As generally accepted in clinical psychology,mental health status can be expressed by behavior,including web behavior. Conventional mental health assessment is performed by self-report inventory, and it requires much manual efforts and cannot be done in real time. We aim to objectively predict user's mental health status,especially depression and anxiety. We confirmed the correlation between personality and mental health status in the conventional theory by examining a set of behavior data on sina microblog environment. Multi-task regression is proposed to predict online user's mental health status. The results indicate that mental health disorders are expressed by specific online behaviors and it is possible to predict user's degree of depression and anxiety through his/her microblog usage.

Key words: depression, anxiety, sina microblog

CLC Number: