Skip to Main Content

Experimental Psychology (Russia)
2020. Vol. 13, no. 1, 149–158
doi:10.17759/exppsy.2020130111
ISSN: 2072-7593 / 2311-7036 (online)

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

446

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

PDF (RUS)
Online translation in english
GS
Information
in Google Scholar

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.

General Information

Keywords: automatic text analysis, personality characteristics, binary classification methods

Journal rubric: Psycholinguistics

Article type: scientific article

DOI: https://doi.org/10.17759/exppsy.2020130111

Funding. This work was partly supported by the Russian Foundation for Basic Research (project No. 17-29-02247 “Development of methods for diagnosing the spread of frustration in network discussions” and project No. 18-00-00233 “Methods for the integrated intellectual analysis of various types of information for social and humanitarian research in social media”).

For citation: Kovalev A.K., Kuznetsova Y.M., Penkina M.Y., Stankevich M.A., Chudova N.V. Possibilities of automatic text analysis in the task of determining the psychological characteristics of the author. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2020. Vol. 13, no. 1, pp. 149–158. DOI: 10.17759/exppsy.2020130111. (In Russ., аbstr. in Engl.)

References

  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.).
  6. Zolotova G.А., Onipenko N.K., Sidorova M.YU. Kommunikativnaya grammatika russkogo yazyka. M.: In-t rus. yaz. RАN im. V.V. Vinogradova, 2004. (In Russ.).
  7. Kovalyov А.K., Kuznetsova YU.M., Minin А.N., Penkina M.YU., Smirnov I.V., Stankevich M.А., CHudova N.V. Metody vyyavleniya po tekstu psikhologicheskikh kharakteristik avtora (na primere agressivnosti) // Voprosy kiberbezopasnosti. 2019, № 4 (32), c. 72—80. (In Russ.).
  8. Litvinova T.А., Litvinova O.А., Ryzhkova E.S., Biryukova E.D., Seredin P.V., Zagorovskaya O.V. Issledovanie vliyaniya pola i psikhologicheskikh kharakteristik avtora na kolichestvennye parametry ego teksta s ispol’zovaniem programmy Linguistic Inquiry and Word Count // Nauchnyj dialog. 2015. № 2 (48). S. 101—109. (In Russ.).
  9. Osipov G.S. Priobretenie znanij intellektual’nymi sistemami: Osnovy teorii i tekhnologii. M.: Nauka, Fizmatlit, 1997. (In Russ.).
  10. Osipov G.S., Smirnov I.V., Tikhomirov I.А. Relyatsionno-situatsionnyj metod poiska i analiza tekstov i ego prilozheniya // Iskusstvennyj intellekt i prinyatie reshenij. 2008. № 2. S. 3—10. (In Russ.).
  11. Esse. Bol’shaya sovetskaya ehntsiklopediya. M.: Sovetskaya ehntsiklopediya 1969-1978. (In Russ.).
  12. Gupta U., Chatterjee A., Srikanth R., & Agrawal P. A Sentiment-and-Semantics-Based Approach for Emotion Detection in Textual Conversations // Neu-IR: Workshop on Neural Information Retrieval, SIGIR 2017, ACM. URL: arXiv:1707.06996.
  13. Pennebaker J., Boyd R., Jordan K., Blackburn K. The development and psychometric properties of LIWC2015. 2015. URL: https://repositories.lib.utexas.edu/bitstream/handle/2152/31333/LIWC2015_ LanguageManual.pdf.

Information About the Authors

Alexey K. Kovalev, Junior Researcher, Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, Moscow, Russia, ORCID: https://orcid.org/0000-0001-7309-7382, e-mail: alexeykkov@gmail.com

Yuliya M. Kuznetsova, PhD in Psychology, Senior Researcher, Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, Moscow, Russia, ORCID: https://orcid.org/0000-0001-9380-4478, e-mail: kuzjum@yandex.ru

Marina Y. Penkina, Senior Lecturer of the Department of General Psychology of the Institute of Experimental Psychology, Moscow State University of Psychology and Education, Moscow, Russia, ORCID: https://orcid.org/0000-0001-7046-6963, e-mail: penkinamju@mgppu.ru

Maksim A. Stankevich, Junior Researcher, Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, Moscow, Russia, ORCID: https://orcid.org/0000-0003-0705-5832, e-mail: maxastan95@gmail.com

Natalia V. Chudova, PhD in Psychology, Senior Researcher, Federal Research Center ‘Computer Science and Control’ of the Russian Academy of Sciences, Moscow, Russia, ORCID: https://orcid.org/0000-0001-9306-1280, e-mail: nchudova@gmail.com

Metrics

Views

Total: 837
Previous month: 15
Current month: 15

Downloads

Total: 446
Previous month: 4
Current month: 3