EXTRACTING RELATIONSHIPS BETWEEN BIG FIVE MODEL AND PERSONALITY CHARACTERISTICS IN SOCIAL NETWORKS

hassanein, mariam and Rady, Sherine and Hussein, Wedad and Gharib, Tarek (2021) EXTRACTING RELATIONSHIPS BETWEEN BIG FIVE MODEL AND PERSONALITY CHARACTERISTICS IN SOCIAL NETWORKS. International Journal of Intelligent Computing and Information Sciences, 21 (2). pp. 41-49. ISSN 2535-1710

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Abstract

Recently, researches focused on studying how the Big Five personality traits are manifested on social networks. These researches proved the presence of relationships between the Big Five Personality traits and various social networks features extracted from users’ generated content. In this paper, the relationships between the Big Five personality traits (Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism) and attributes of personality characteristics identified as the Personal Values and Human Needs. These attributes or namely features, are extracted from users’ posts on social media. The relationship between the traits and proposed attributes is investigated through Pearson correlation coefficients. A dataset for 564 Twitter users is used in an experimental study, where findings proved the presence of relevant correlations between the traits and the proposed personality characteristic features. The Conscientiousness, Agreeableness, and Neuroticism traits showed strong relations existence with all of the Personal Values features, while the Openness to experience and Neuroticism traits showed strong correlations with Liberty and Self-expression Needs features consecutively. The proposed study verified the effectiveness of the proposed Personal Values and Human Needs features as indicators for the Big Five personality traits, proving their ability for personality characteristics classification.

Item Type: Article
Subjects: STM Library > Computer Science
Depositing User: Managing Editor
Date Deposited: 28 Jun 2023 04:20
Last Modified: 20 Oct 2023 04:08
URI: http://open.journal4submit.com/id/eprint/2414

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