A Survey of Psychological Personality Classification Approaches

Authors

Mervat Ragab Bakry, Faculty of Computers and Artificial Intelligence, Beni-Suef University, EgyptFollow
Mona Mohamed Nasr, Faculty of Computers and Artificial Intelligence, Helwan University, EgyptFollow
Fahad Kamal Al-sheref, Faculty of Computers and Artificial Intelligence, Beni-Suef University, EgyptFollow

DOI

http://doi.org/10.54623/fue.fcij.4.2.3

Abstract

Online social networks (OSNs) have become essential ways for users to socially share information and feelings, communicate, and thoughts with others through online social networks. Online social networks such as Twitter and Facebook are some of the most common OSNs among users. Users’ behaviors on social networks aid researchers for detecting and understanding their online behaviors and personality traits. Personality detection is one of the new difficulties in social networks. Machine learning techniques are used to build models for understanding personality, detecting personality traits, and classifying users into different kinds through user generated content based on different features and measures of psychological models such as PEN (Psychoticism, Extraversion, and Neuroticism) model, DISC (Dominance, Influence, Steadiness, and Compliance) model, and the Big-five model (Openness, Extraversion, Consciousness, Agreeableness, and Neurotic) which is the most accepted model of personality. This survey discusses the existing works on psychological personality classification.

Recommended Citation

Bakry, Mervat Ragab; Nasr, Mona Mohamed; and Al-sheref, Fahad Kamal (2019) "A Survey of Psychological Personality Classification Approaches," Future Computing and Informatics Journal: Vol. 4: Iss. 2, Article 3.
DOI: http://doi.org/10.54623/fue.fcij.4.2.3
Available at: https://digitalcommons.aaru.edu.jo/fcij/vol4/iss2/3