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SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research.

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A Multi-Faceted NLP Analysis of Misinformation Spreaders in Twitter., , and . WASSA, page 71-83. Association for Computational Linguistics, (2024)COVID-19 and Misinformation: A Large-Scale Lexical Analysis on Twitter., , , and . ACL (student), page 119-126. Association for Computational Linguistics, (2021)BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages., , , , , , , , , and 12 other author(s). CoRR, (2024)Twitter Topic Classification., , , , , and . COLING, page 3386-3400. International Committee on Computational Linguistics, (2022)TweetNLP: Cutting-Edge Natural Language Processing for Social Media., , , , , , , , , and . EMNLP (Demos), page 38-49. Association for Computational Linguistics, (2022)Words as Trigger Points in Social Media Discussions., , , , and . CoRR, (2024)TweetNLP: Cutting-Edge Natural Language Processing for Social Media., , , , , , , , , and 4 other author(s). CoRR, (2022)Multilingual Topic Classification in X: Dataset and Analysis, , , and . (2024)Negativity spreads faster: A large-scale multilingual twitter analysis on the role of sentiment in political communication., , and . Online Soc. Networks Media, (2023)SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research., , , , , , , and . EMNLP (Findings), page 12590-12607. Association for Computational Linguistics, (2023)