论文标题

关于基于文本的个性计算:挑战和未来方向

On Text-based Personality Computing: Challenges and Future Directions

论文作者

Fang, Qixiang, Giachanou, Anastasia, Bagheri, Ayoub, Boeschoten, Laura, van Kesteren, Erik-Jan, Kamalabad, Mahdi Shafiee, Oberski, Daniel L

论文摘要

基于文本的人格计算(TPC)在NLP中获得了许多研究兴趣。在本文中,我们描述了我们考虑值得研究社区注意的15个挑战。这些挑战是由以下主题组织的:人格分类法,测量质量,数据集,绩效评估,建模选择以及道德和公平。在解决每个挑战时,我们不仅结合了NLP和社会科学的观点,而且还提供了具体的建议。我们希望激发更有效和可靠的TPC研究。

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.

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