期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2021
卷号：2021
页码：1921-1945
DOI：10.18653/v1/2021.eacl-main.165
语种：English
出版社：ACL Anthology
摘要：Computational modelling of political discourse tasks has become an increasingly important area of research in the field of natural language processing. Populist rhetoric has risen across the political sphere in recent years; however, due to its complex nature, computational approaches to it have been scarce. In this paper, we present the new Us vs. Them dataset, consisting of 6861 Reddit comments annotated for populist attitudes and the first large-scale computational models of this phenomenon. We investigate the relationship between populist mindsets and social groups, as well as a range of emotions typically associated with these. We set a baseline for two tasks associated with populist attitudes and present a set of multi-task learning models that leverage and demonstrate the importance of emotion and group identification as auxiliary tasks.
