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Application of social networks users digital fingerprints to predict their information image

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Published:29 October 2020Publication History

ABSTRACT

This paper is devoted to detection of correlations between the information image of users in social network and their real psychological personality traits and personal details. The ongoing research consists of psychodiagnostic testing of social media users, as well as further collection and processing of their open data in the social media profile. The interim results of our ongoing research allow us to conclude that there are significant patterns that allow us to determine age, gender or level of education by user' avatar and other public data in their profiles.

References

  1. Chen Y, Pavlov D, Canny J.F. 2009. Large-scale behavioral targeting. International Conference on Knowledge Discovery and Data Mining, 209--218.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Kosinski M., Matz S., Gosling S. et al. 2015. Facebook as a social science research tool: Opportunities, challenges, ethical considerations and practical guidelines.. American Psychologist. 70, 6, 543--556.Google ScholarGoogle ScholarCross RefCross Ref
  3. Xenos S., Ryan T. 2011. Who uses Facebook? An investigation into the relationship between the Big Five, shyness, narcissism, loneliness, and Facebook usage. Computers in Human Be-havior. 27, 5. 1658--1664.Google ScholarGoogle Scholar
  4. Kosinski M., Stilwell D., Graepel T. 2013. Private traits and attributes are predictable from digital records of human behaviour. Proc. the National Academy of Science of the United State of America. 2013. 110. 5802--5805. DOI: 10.1073/pnas.1218772110Google ScholarGoogle Scholar
  5. Ross C., Orr E.S., Sisic M., Arseneault J.M., Simmering M.G., Orr R.R. 2009. Personality and motivations associated with facebook use. Computers in Human Behavior. 25. 578--586. DOI: 10.1016/j.chb.2008.12.024Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Krylova O.S., Vlasov D.A., Shishkov V.V., Alymov A.S., Ishin I.A., Kolesnikov I.E. Petrov A.I. 2018. Opisanie informacionnogo obraza pol'zovatelya social'noj seti s uchetom ego psihologicheskoj harakteristiki // International Journal of Open Information Technologies. 4. 24--37.Google ScholarGoogle Scholar
  7. Mairesse F., Walker M., Mehl M., Moore R. 2007. Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research. 30. 457--500. DOI: 10.1613/jair.2349Google ScholarGoogle Scholar

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  1. Application of social networks users digital fingerprints to predict their information image

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    • Published in

      cover image ACM Other conferences
      ICEGOV '20: Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance
      September 2020
      880 pages
      ISBN:9781450376747
      DOI:10.1145/3428502

      Copyright © 2020 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 29 October 2020

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      • short-paper
      • Research
      • Refereed limited

      Acceptance Rates

      ICEGOV '20 Paper Acceptance Rate79of209submissions,38%Overall Acceptance Rate350of865submissions,40%

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