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.
@article{arxiv.2110.01186,
title = {Text-based automatic personality prediction: A bibliographic review},
author = {Ali-Reza Feizi-Derakhshi and Mohammad-Reza Feizi-Derakhshi and Majid Ramezani and Narjes Nikzad-Khasmakhi and Meysam Asgari-Chenaghlu and Taymaz Akan and Mehrdad Ranjbar-Khadivi and Elnaz Zafarni-Moattar and Zoleikha Jahanbakhsh-Naghadeh},
journal= {arXiv preprint arXiv:2110.01186},
year = {2022}
}
Comments
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