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Text-based automatic personality prediction: a bibliographic review

Authors :
Feizi-Derakhshi, Ali-Reza
Feizi-Derakhshi, Mohammad-Reza
Ramezani, Majid
Nikzad-Khasmakhi, Narjes
Asgari-Chenaghlu, Meysam
Akan, Taymaz
Ranjbar-Khadivi, Mehrdad
Zafarni-Moattar, Elnaz
Jahanbakhsh-Naghadeh, Zoleikha
Source :
Journal of Computational Social Science; 20220101, Issue: Preprints p1-39, 39p
Publication Year :
2022

Abstract

Personality detection is an old topic in psychology and automatic personality prediction (or perception) (APP) is the automated (computationally) forecasting of the personality on different types of human generated/exchanged contents (such as text, speech, image, and video). The principal objective of this study is to offer a shallow (overall) review of natural language processing approaches on APP since 2010. With the advent of deep learning and following it transfer-learning and pre-trained model in NLP, APP research area has been a hot topic, so in this review, methods are categorized into three: pre-trained independent, pre-trained model based, and multimodal approaches. In addition, to achieve a comprehensive comparison, reported results are informed by datasets.

Details

Language :
English
ISSN :
24322717 and 24322725
Issue :
Preprints
Database :
Supplemental Index
Journal :
Journal of Computational Social Science
Publication Type :
Periodical
Accession number :
ejs60701802
Full Text :
https://doi.org/10.1007/s42001-022-00178-4