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Personality Identification from Social Media Using Deep Learning: A Review

  • S. BhavyaEmail author
  • Anitha S. Pillai
  • Giuliana Guazzaroni
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1057)

Abstract

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed.

Keywords

Deep learning Five-factor model Conscientiousness Openness Extraversion Neuroticism Personality recognition Online social media 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • S. Bhavya
    • 1
    Email author
  • Anitha S. Pillai
    • 1
  • Giuliana Guazzaroni
    • 2
  1. 1.School of Computing SciencesHindustan Institute of Technology and ScienceChennaiIndia
  2. 2.Marche Polytechnic UniversityAnconaItaly

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