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Computational modelling of political discourse tasks has become anincreasingly 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 complexnature. In this paper, we present the new $\textit{Us vs. Them}$ dataset,consisting of 6861 Reddit comments annotated for populist attitudes and thefirst large-scale computational models of this phenomenon. We investigate therelationship between populist mindsets and social groups, as well as a range ofemotions typically associated with these. We set a baseline for two tasksrelated to populist attitudes and present a set of multi-task learning modelsthat leverage and demonstrate the importance of emotion and groupidentification as auxiliary tasks.

Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions