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Personality Analysis Using Classification on Turkish Tweets

Author

Listed:
  • Gokalp Mavis

    (Middle East Technical University, Turkey)

  • Ismail Hakki Toroslu

    (Middle East Technical University, Turkey)

  • Pinar Karagoz

    (Middle East Technical University, Turkey)

Abstract

According to the psychology literature, there is a strong correlation between the personality traits and the linguistic behavior of people. Due to increase in computer based communication, individuals express their personalities in written forms on social media. Hence, social media became a convenient resource to analyze the relationship between the personality traits and the lingusitic behaviour. Although there is a vast amount of studies on social media, only a small number of them focus on personality prediction. In this work, we aim to model the relationship between the social media messages of individuals and Big Five Personality Traits as a supervised learning problem. We use Twitter posts and user statistics for analysis. We investigated various approaches for user profile representation, explored several supervised learning techniques, and presented comparative analysis results. Our results confirm the findings of psychology literature, and we show that computational analysis of tweets using supervised learning methods can be used to determine the personality of individuals.

Suggested Citation

  • Gokalp Mavis & Ismail Hakki Toroslu & Pinar Karagoz, 2021. "Personality Analysis Using Classification on Turkish Tweets," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 15(4), pages 1-18, October.
    • Handle: RePEc:igg:jcini0:v:15:y:2021:i:4:p:1-18
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    References listed on IDEAS

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    1. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    2. Odekerken-Schroder, Gaby & De Wulf, Kristof & Schumacher, Patrick, 2003. "Strengthening outcomes of retailer-consumer relationships: The dual impact of relationship marketing tactics and consumer personality," Journal of Business Research, Elsevier, vol. 56(3), pages 177-190, March.
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    Cited by:

    1. Mohmad Azhar Teli & Manzoor Ahmad Chachoo, 2022. "Lingual markers for automating personality profiling: background and road ahead," Journal of Computational Social Science, Springer, vol. 5(2), pages 1663-1707, November.
    2. Wanxin Chen & Xiao Chen*, 2022. "Developmental Trajectory of the American Yacht Clubs: Using Temporal‐Spatial Analysis and Regression Model," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 16(1), pages 1-15, January.

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