Depression detection from social media profiles

The problem of early depression detection is one of the most important in the field of psychology. Social network analysis is widely applied to address this problem. In this paper, we consider the task of automatic detection of depression signs from textual messages and profile information of Russian social network VKontakte users. We describe the preparation of users’ profiles dataset and propose linguistic and profile information based features. We evaluate several machine learning methods and report experiments results. The best performance in our experiments achieved by the model that was trained on features that reflects information about users’ subscriptions on Vkontakte groups and communities. © Springer Nature Switzerland AG 2020.

Authors
Stankevich M. 1 , Smirnov I. 1, 2 , Kiselnikova N.3 , Ushakova A.4
Publisher
Springer Verlag
Language
English
Pages
181-194
Status
Published
Volume
1223 CCIS
Year
2020
Organizations
  • 1 Federal Research Center “Computer Science and Control” of RAS, Moscow, Russian Federation
  • 2 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 3 Psychological Institute, Russian Academy of Education, Moscow, Russian Federation
  • 4 Moscow Institute of Physics and Technology, Moscow, Russian Federation
Keywords
Depression detection; Psycholinguistics; Social networks
Date of creation
02.11.2020
Date of change
02.11.2020
Short link
https://repository.rudn.ru/en/records/article/record/65568/
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