Recent Trends in Deep Learning Based Personality Detection
Abstract
Recently, the automatic prediction of personality traits has received a lot of attention. Specifically, personality trait prediction from multimodal data has emerged as a hot topic within the field of affective computing. In this paper, we review significant machine learning models which have been employed for personality detection, with an emphasis on deep learning-based methods. This review paper provides an overview of the most popular approaches to automated personality detection, various computational datasets, its industrial applications, and state-of-the-art machine learning models for personality detection with specific focus on multimodal approaches. Personality detection is a very broad and diverse topic: this survey only focuses on computational approaches and leaves out psychological studies on personality detection.
Cite
@article{arxiv.1908.03628,
title = {Recent Trends in Deep Learning Based Personality Detection},
author = {Yash Mehta and Navonil Majumder and Alexander Gelbukh and Erik Cambria},
journal= {arXiv preprint arXiv:1908.03628},
year = {2020}
}