TY - JOUR
T1 - Recent trends in deep learning based personality detection
AU - Mehta, Yash
AU - Majumder, Navonil
AU - Gelbukh, Alexander
AU - Cambria, Erik
N1 - Publisher Copyright:
© 2019, Springer Nature B.V.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - 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.
AB - 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.
KW - Deep learning
KW - Multimodal interaction
KW - Personality detection
UR - http://www.scopus.com/inward/record.url?scp=85074520909&partnerID=8YFLogxK
U2 - 10.1007/s10462-019-09770-z
DO - 10.1007/s10462-019-09770-z
M3 - Artículo
AN - SCOPUS:85074520909
SN - 0269-2821
VL - 53
SP - 2313
EP - 2339
JO - Artificial Intelligence Review
JF - Artificial Intelligence Review
IS - 4
ER -