Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions
- URL: http://arxiv.org/abs/2101.11956v1
- Date: Thu, 28 Jan 2021 12:18:19 GMT
- Title: Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions
- Authors: Pere-Llu\'is Huguet Cabot, David Abadi, Agneta Fischer, Ekaterina
Shutova
- Abstract summary: We present the new Us vs. Them dataset, consisting of 6861 Reddit comments annotated for populist attitudes.
We investigate the relationship between populist mindsets and social groups, as well as a range of emotions typically associated with these.
We present a set of multi-task learning models that leverage and demonstrate the importance of emotion and group identification as auxiliary tasks.
- Score: 10.112779201155005
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Computational modelling of political discourse tasks has become an
increasingly important area of research in natural language processing.
Populist rhetoric has risen across the political sphere in recent years;
however, computational approaches to it have been scarce due to its complex
nature. 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 related to
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.
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