Text-based automatic personality prediction: A bibliographic review

Autor:	Ali-Reza Feizi-Derakhshi, Mohammad-Reza Feizi-Derakhshi, Majid Ramezani, Narjes Nikzad-Khasmakhi, Meysam Asgari-Chenaghlu, Taymaz Akan, Mehrdad Ranjbar-Khadivi, Elnaz Zafarni-Moattar, Zoleikha Jahanbakhsh-Naghadeh
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	FOS: Computer and information sciences Artificial Intelligence (cs.AI) Computer Science - Computation and Language Artificial Intelligence Computer Science - Artificial Intelligence Transportation Computation and Language (cs.CL)
Popis:	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. 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
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ea66a956b2fca69126f51edcf8dbd72 http://arxiv.org/abs/2110.01186 Zobrazit plný text záznamu