2024 COLING COLING 2024

PopAut: An Annotated Corpus for Populism Detection in Austrian News Comments

Abstract

AbstractPopulism is a phenomenon that is noticeably present in the political landscape of various countries over the past decades. While populism expressed by politicians has been thoroughly examined in the literature, populism expressed by citizens is still underresearched, especially when it comes to its automated detection in text. This work presents the PopAut corpus, which is the first annotated corpus of news comments for populism in the German language. It features 1,200 comments collected between 2019-2021 that are annotated for populist motives anti-elitism, people-centrism and people-sovereignty. Following the definition of Cas Mudde, populism is seen as a thin ideology. This work shows that annotators reach a high agreement when labeling news comments for these motives. The data set is collected to serve as the basis for automated populism detection using machine-learning methods. By using transformer-based models, we can outperform existing dictionaries tailored for automated populism detection in German social media content. Therefore our work provides a rich resource for future work on the classification of populist user comments in the German language.

๐ŸŒ‰ Interdisciplinary Bridge โ€” Deep Learning and Machine Learning
๐Ÿงญ Keyword Pioneer โ€” populism detection
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio