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

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Findings: Computational Social Science and Cultural Analytics Findings Paper

Session 7: Computational Social Science and Cultural Analytics (Virtual Poster)
Conference Room: Pier 7&8
Conference Time: July 12, 11:00-12:30 (EDT) (America/Toronto)
Global Time: July 12, Session 7 (15:00-16:30 UTC)
Spotlight Session: Spotlight - Metropolitan East (Spotlight)
Conference Room: Metropolitan East
Conference Time: July 10, 19:00-21:00 (EDT) (America/Toronto)
Global Time: July 10, Spotlight Session (23:00-01:00 UTC)
Keywords: psycho-demographic trait prediction
TLDR: 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, data...
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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.