Abstract
Personality profiling has long been used in psychology to predict life outcomes. Recently, automatic detection of personality traits from written messages has gained significant attention in computational linguistics and natural language processing communities, due to its applicability in various fields. In this survey, we show the trajectory of research towards automatic personality detection from purely psychology approaches, through psycholinguistics, to the recent purely natural language processing approaches on large datasets automatically extracted from social media. We point out what has been gained and what lost during that trajectory, and show what can be realistic expectations in the field.- Anthology ID:
- 2020.coling-main.553
- Volume:
- Proceedings of the 28th International Conference on Computational Linguistics
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 6284–6295
- Language:
- URL:
- https://aclanthology.org/2020.coling-main.553
- DOI:
- 10.18653/v1/2020.coling-main.553
- Cite (ACL):
- Sanja Stajner and Seren Yenikent. 2020. A Survey of Automatic Personality Detection from Texts. In Proceedings of the 28th International Conference on Computational Linguistics, pages 6284–6295, Barcelona, Spain (Online). International Committee on Computational Linguistics.
- Cite (Informal):
- A Survey of Automatic Personality Detection from Texts (Stajner & Yenikent, COLING 2020)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/2020.coling-main.553.pdf