On Text-based Personality Computing: Challenges and Future Directions
This work addresses methodological and ethical issues in text-based personality computing for NLP researchers, but it is incremental as it synthesizes existing challenges rather than presenting new empirical results.
The paper identifies 15 key challenges in text-based personality computing, such as personality taxonomies and ethics, and offers interdisciplinary suggestions to inspire more valid and reliable research in this field.
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 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.