Predicting depression from essays in Russian [ВЫЯВЛЕНИЕ ПРИЗНАКОВ ДЕПРЕССИИ У АВТОРОВ ЭССЕ НА РУССКОМ ЯЗЫКЕ]

The study is focused on the detection of depression by processing and classification of short essays written by 316 volunteers. The set of 93 essays was provided by two different teams of psychologists who asked patients with clinically confirmed depression to write short essays on the neutral topic. The other 223 essays on the same topic were written by volunteers who completed questionnaires, which are designed to reveal depression status and did not demonstrate any signs of mental illnesses. The study describes psycholinguistic and classic text features which were calculated by utilizing natural language processing tools and were used to perform on the classification task. The machine learning classification models achieved up to 73% of f1-score for the task of revealing essays written by people with depression. © 2019 ABBYY PRODUCTION LLC. All rights reserved.

Authors
Stankevich M.A.1 , Smirnov I.V. 2 , Kuznetsova Y.M.1 , Kiselnikova N.V.3 , Enikolopov S.N.4
Publisher
Rossiiskii Gosudarstvennyi Gumanitarnyi Universitet
Number of issue
18
Language
English
Pages
647-657
Status
Published
Volume
2019-May
Year
2019
Organizations
  • 1 Artificial Intelligence Research Institute, FRC CSC RAS, Moscow, Russian Federation
  • 2 Artificial Intelligence Research Institute, FRC CSC RAS, Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 3 Psychological Institute of Russian Academy of Education, Moscow, Russian Federation
  • 4 Department of Medical Psychology, Mental Health Research Centre, Moscow, Russian Federation
Keywords
Depression detection; Natural language processing; Psycholinguistic features; Text classification
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