Personality Analysis Using Classification on Turkish Tweets


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Mavis G., TOROSLU İ. H. , KARAGÖZ P.

International Journal of Cognitive Informatics and Natural Intelligence, vol.15, 2021 (ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 15
  • Publication Date: 2021
  • Doi Number: 10.4018/ijcini.287596
  • Journal Name: International Journal of Cognitive Informatics and Natural Intelligence
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Psycinfo, Civil Engineering Abstracts
  • Keywords: Big Five Personality Traits, Deep Learning, Machine Learning, Personality, Social Media, Supervised Learning, Tweets
  • Middle East Technical University Affiliated: Yes

Abstract

According to the psychology literature, there is a strong correlation between personality traits and the linguistic behavior of people. Due to the increase in computer based communication, individuals express their personalities in written forms on social media. Hence, social media has become a convenient resource to analyze the relationship between personality traits and 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, the authors aim to model the relationship between the social media messages of individuals and big five personality traits as a supervised learning problem. They use Twitter posts and user statistics for analysis. They investigate various approaches for user profile representation, explore several supervised learning techniques, and present comparative analysis results. The results confirm the findings of psychology literature, and they show that computational analysis of tweets using supervised learning methods can be used to determine the personality of individuals.