On Text-based Personality Computing: Challenges and Future Directions
Qixiang Fang, Anastasia Giachanou, Ayoub Bagheri, Laura Boeschoten, Erik-Jan van Kesteren, Mahdi Shafiee Kamalabad, Daniel Oberski
Abstract
Text-based personality computing (TPC) has gained many research interests in NLP. In this paper, we describe 15 challenges that we consider deserving the attention of the NLP research community. These challenges are organized by the following topics: personality taxonomies, measurement quality, datasets, performance evaluation, modelling choices, as well as ethics and fairness. When addressing each challenge, not only do we combine perspectives from both NLP and social sciences, but also offer concrete suggestions. We hope to inspire more valid and reliable TPC research.- Anthology ID:
- 2023.findings-acl.691
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2023
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10861–10879
- Language:
- URL:
- https://aclanthology.org/2023.findings-acl.691
- DOI:
- 10.18653/v1/2023.findings-acl.691
- Cite (ACL):
- Qixiang Fang, Anastasia Giachanou, Ayoub Bagheri, Laura Boeschoten, Erik-Jan van Kesteren, Mahdi Shafiee Kamalabad, and Daniel Oberski. 2023. On Text-based Personality Computing: Challenges and Future Directions. In Findings of the Association for Computational Linguistics: ACL 2023, pages 10861–10879, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- On Text-based Personality Computing: Challenges and Future Directions (Fang et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.findings-acl.691.pdf