The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Recent trends in deep learning based personality detection
Open accessAbstract
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.
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Cites
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ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis
Basiri, M. E., Nemati, S., Abdar, M., Cambria, E., & Acharya, U. R. (2021) · Future Generation Computer Systems · doi:10.1016/j.future.2020.08.005 · Cited by 745
Self-citationPANDORA Talks: Personality and Demographics on Reddit
Gjurković, M., Karan, M., Vukojević, I., Bošnjak, M., & Snajder, J. (2021) · Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media · doi:10.18653/v1/2021.socialnlp-1.12 · Cited by 58
Kaur, P., Dhir, A., Alkhalifa, A. K., & Tandon, A. (2021) · Internet Research · doi:10.1108/intr-04-2020-0187 · Cited by 55
Metadata
- Authors
- Mehta, Y., Majumder, N., Gelbukh, A., & Cambria, E.
- Venue
- Artificial Intelligence Review
- Published
- 2019-10-10
- Volume
- 53
- Issue
- 4
- Pages
- 2313-2339
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W2969145558
- Cited by
- 329
- References
- 15
- FWCI
- 44.48
- Type
- journal article
- Language
- en
- Open access
- green
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