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Recent trends in deep learning based personality detection

  • Yash Mehta
  • Navonil Majumder
  • Alexander Gelbukh
  • Erik CambriaEmail author
Article

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.

Keywords

Personality detection Multimodal interaction Deep learning 

Notes

Acknowledgements

We would like to thank Prof. Bharat M Deshpande for his valuable guidance. A. Gelbukh recognizes the support of the Instituto Politecnico Nacional via the Secretaria de Investigacion y Posgrado projects SIP 20196437 and SIP 20196021.

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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Gatsby Computational Neuroscience UnitUniversity College LondonLondonUK
  2. 2.Centro de Investigación en ComputaciónInstituto Politécnico NacionalMexico CityMexico
  3. 3.School of Computer Science and EngineeringNanyang Technological UniversitySingaporeSingapore

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