Possibilities of automatic text analysis in the task of determining the psychological characteristics of the author

Author:

Kovalev A.K.1ORCID,Kuznetsova Y.M.1ORCID,Penkina M.Y.2ORCID,Stankevich M.A.1ORCID,Chudova N.V.1ORCID

Affiliation:

1. Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences

2. Moscow State University of Psychology and Education

Abstract

Using a tool for automatic text analysis and machine learning methods developed at the Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, the first results are obtained in the task of identifying text parameters specific to people with certain psychological characteristics. The tool of corpus linguistic and statistical research, based on the use of relational-situational analysis, psycholinguistic indicators and dictionaries covering the vocabulary of emotional and rational assessment, allowed us to obtain values for 177 textual attributes of the essay written by 486 subjects. To obtain data on the severity of characterological and personality characteristics of the subjects, a number of psychological questionnaires were used. When processing the data, binary classification algorithms were used — the support vector method (SVM) and the Random Forest method. The results allow us to draw conclusions about the prospects of using some textual parameters in problems of population psychodiagnostics and the adequacy of the applied classification algorithms.

Funder

Russian Foundation for Basic Research

Publisher

Federal State-Financed Educational Institution of Higher Education Moscow State University of Psychology and Education

Reference13 articles.

1. Аlmaev N.А., Dorodnev А.B., Malkova G.YU. Proyavlenie psikhologicheskoj travmy v avtobiograficheskikh rasskazakh // EHksperimental’naya psikhologiya. 2009. Tom 2. № 2. S. 104—115. (In Russ.).

2. Vorontsova O.YU., Enikolopov S.N., Kuznetsova YU.M., CHudova N.V. i dr. Lingvisticheskie kharakteristiki tekstov psikhicheski bol’nykh i zdorovykh lyudej // Psikhologicheskie issledovaniya. 2018. T. 11. № 61. URL: http://psystudy.ru/index.php/num/2018v11n61/1622-enikolopov61.html. (In Russ.).

3. Devyatkin D.А., Kuznetsova YU.M., CHudova, N.V., SHvets А.V. Intellektual’nyj analiz proyavlenij verbal’noj agressivnosti v tekstakh setevykh soobshhestv // Iskusstvennyj intellekt i prinyatie reshenij. 2014, №2, s. 95—109. (In Russ.).

4. Enikolopov S.N., Kuznetsova YU.M., Smirnov I.V., Stankevich M.А., CHudova N.V. Sozdanie instrumenta avtomaticheskogo analiza teksta v interesakh sotsio-gumanitarnykh issledovanij. CH. 1. Metodicheskie i metodologicheskie aspekty // Iskusstvennyj intellekt i prinyatie reshenij. 2019. № 2, Str. 28-38. DOI 10.14357/20718594190203. (In Russ.).

5. Enikolopov S.N., Kuznetsova YU.M., Minin А.N., Penkina M.YU., Smirnov I.V., Stankevich M.А., CHudova N.V. Osobennosti teksta i psikhologicheskie osobennosti: opyt ehmpiricheskogo komp’yuternogo issledovaniya // Trudy ISА RАN, 2019, № 3 (v pechati). (In Russ.).

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