Text-based automatic personality prediction: a bibliographic review

Ali-Reza Feizi-Derakhshi (), Mohammad-Reza Feizi-Derakhshi (), Majid Ramezani (), Narjes Nikzad-Khasmakhi (), Meysam Asgari-Chenaghlu (), Taymaz Akan (), Mehrdad Ranjbar-Khadivi (), Elnaz Zafarni-Moattar () and Zoleikha Jahanbakhsh-Naghadeh ()
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Ali-Reza Feizi-Derakhshi: University of Tabriz
Mohammad-Reza Feizi-Derakhshi: University of Tabriz
Majid Ramezani: University of Tabriz
Narjes Nikzad-Khasmakhi: University of Tabriz
Meysam Asgari-Chenaghlu: University of Tabriz
Taymaz Akan: University of Tabriz
Mehrdad Ranjbar-Khadivi: University of Tabriz
Elnaz Zafarni-Moattar: University of Tabriz
Zoleikha Jahanbakhsh-Naghadeh: University of Tabriz

Journal of Computational Social Science, 2022, vol. 5, issue 2, No 17, 1555-1593

Abstract: 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.

Keywords: Automatic personality prediction; Natural language processing (NLP); Text mining; Personality trait (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s42001-022-00178-4

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