Faramarzi, Noushin Salek, authorChaleshtori, Fateme Hashemi, authorShirazi, Hossein, authorRay, Indrakshi, authorBanerjee, Ritwik, authorACM, publisher2024-11-112024-11-112023-04-30Noushin Salek Faramarzi, Fateme Hashemi Chaleshtori, Hossein Shirazi, Indrakshi Ray, and Ritwik Banerjee. 2023. Claim Extraction and Dynamic Stance Detection in COVID-19 Tweets. In Companion Proceedings of the ACM Web Conference 2023 (WWW '23 Companion), April 30–May 04, 2023, Austin, TX, USA. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3543873.3587643https://hdl.handle.net/10217/239529The information ecosystem today is noisy, and rife with messages that contain a mix of objective claims and subjective remarks or reactions. Any automated system that intends to capture the social, cultural, or political zeitgeist, must be able to analyze the claims as well as the remarks. Due to the deluge of such messages on social media, and their tremendous power to shape our perceptions, there has never been a greater need to automate these analyses, which play a pivotal role in fact-checking, opinion mining, understanding opinion trends, and other such downstream tasks of social consequence. In this noisy ecosystem, not all claims are worth checking for veracity. Such a check-worthy claim, moreover, must be accurately distilled from subjective remarks surrounding it. Finally, and especially for understanding opinion trends, it is important to understand the stance of the remarks or reactions towards that specific claim. To this end, we introduce a COVID-19 Twitter dataset, and present a three-stage process to (i) determine whether a given Tweet is indeed check-worthy, and if so, (ii) which portion of the Tweet ought to be checked for veracity, and finally, (iii) determine the author's stance towards the claim in that Tweet, thus introducing the novel task of topic-agnostic stance detection.born digitalarticleseng©Noushin Salek Faramarzi, et al. ACM 2023. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in WWW '23 Companion, https://dx.doi.org/10.1145/3543873.3587643.stance detectionclaim extractionCOVID-19Texthttps://doi.org/10.1145/3543873.3587643