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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
Publication Year :
2021

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, 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, multimodal approaches. Also, to achieve a comprehensive comparison, reported results are informed by datasets.<br />Comment: This is a preprint of an article published in "Journal of Computational Social Science". The final authenticated version is available online at: https://doi.org/10.1007/s42001-022-00178-4

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2110.01186
Document Type :
Working Paper
Full Text :
https://doi.org/10.1007/s42001-022-00178-4