The state-of-the-art in text-based automatic personality prediction

• URL: http://arxiv.org/abs/2110.01186v1
• Date: Mon, 4 Oct 2021 04:51:11 GMT
• Title: The state-of-the-art in text-based automatic personality prediction
• Authors: Ali-Reza Feizi-Derakhshi, Mohammad-Reza Feizi-Derakhshi, Majid Ramezani, Narjes Nikzad-Khasmakhi, Meysam Asgari-Chenaghlu, Taymaz Akan (Rahkar-Farshi), Mehrdad Ranjbar-Khadivi, Elnaz Zafarni-Moattar, Zoleikha Jahanbakhsh-Naghadeh
• Abstract summary: Personality detection is an old topic in psychology and Automatic Personality Prediction (or Perception) (APP) APP is the automated (computationally) forecasting of the personality on different types of human generated/exchanged contents (such as text, speech, image, video)
• Score: 1.3209941988151326
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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.

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