Heinrich P, Blombach A, Doan Dang B, Zilio L, Havenstein L, Dykes N, Evert S, Schäfer F (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: European Language Resources Association (ELRA)
Pages Range: 1932-1943
Conference Proceedings Title: LREC-COLING 2024 - Main Conference Proceedings
ISBN: 9782493814104
We are concerned with mapping the discursive landscape of conspiracy narratives surrounding the COVID-19 pandemic. In the present study, we analyse a corpus of more than 1,000 German Telegram posts manually tagged with 14 conspiracy and conspiracy-related narrative labels by three independent annotators. Since emerging narratives on social media are short-lived and notoriously hard to track, we experiment with different state-of-the-art approaches to few-shot and zero-shot text classification. We report performance in terms of ROC-AUC and in terms of optimal F1, and compare fine-tuned methods with off-the-shelf approaches and human performance.
APA:
Heinrich, P., Blombach, A., Doan Dang, B., Zilio, L., Havenstein, L., Dykes, N.,... Schäfer, F. (2024). Automatic Identification of COVID-19-related Narratives in German Telegram Channels and Chats. In Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue (Eds.), LREC-COLING 2024 - Main Conference Proceedings (pp. 1932-1943). Torino, IT: European Language Resources Association (ELRA).
MLA:
Heinrich, Philipp, et al. "Automatic Identification of COVID-19-related Narratives in German Telegram Channels and Chats." Proceedings of the Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024, Torino Ed. Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue, European Language Resources Association (ELRA), 2024. 1932-1943.
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