Recent trends in deep learning based personality detection

By Yash Mehta, Navonil Majumder, Alexander Gelbukh, Erik Cambria. Artificial Intelligence Review, 2019

300 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Clinical Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/677abf4f5c523fe93ee2d5848c1321430defff09

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Frank Xing
2. Yukun Ma
3. Erik Cambria
4. Shaoxiong Ji
5. K. L. Nguyen
6. Prayag Tiwari
7. Jie Fu
8. Tianlin Zhang

In Clinical Psychology

1. Erik Cambria

In Experimental and Cognitive Psychology

1. Frank Xing
2. Prayag Tiwari
3. Erik Cambria
4. Soujanya Poria
5. Devamanyu Hazarika
6. Louis-philippe Morency
7. Navonil Majumder
8. Amir Zadeh

Citations in the corpus

• A survey on empathetic dialogue systems (2020, background): “, old people versus young people) [85], personality (introverts versus extroverts) [104], or gender (woman versus man) [89] that are mostly not part of a visible context.”
• MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare (2021, background): “, 2022), personality detection (Mehta et al., 2020), and social media analysis (Grassi et al.”