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While previous studies investigated the factors that affect people's perceptions of information credibility and how laypeople's judgements compare to experts, little is known about how the information credibility assessment work is performed and cooperated by individuals and communities in real-life, natural online environments. Through a qualitative study of an online community, r\/DebunkThis, which is dedicated to information debunking, we found that online information debunking rarely followed a linear and straightforward path. Rather, community members, including the debunkers and the original posters, constantly negotiated, and interacted with each other to determine what to debunk and how to debunk. Individuals adopted various strategies to debunk information, such as questioning the credibility of the information source and citing authoritative external information. Community members supplemented with details and explanations, corrected others, requested clarifications, summarized high-level knowledge and skills, and interacted socially based on individuals' debunking explanations. Our study results broaden the understanding of debunking not only as an outcome but also as a learning and social process for community members to learn high-level debunking skills and form and enforce community rules. We provide implications for designing community and crowd-based information debunking systems which should recognize the complex, cooperative, and socially situated work of community and crowd debunkers. The design of such systems should therefore support not only labeling information as correct or not or simply sharing alternative information sources, but also community interactions and learning processes, as well as recognizing the labor of community debunkers.<\/jats:p>","DOI":"10.1145\/3555138","type":"journal-article","created":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T22:59:06Z","timestamp":1668207546000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Help Me #DebunkThis: Unpacking Individual and Community's Collaborative Work in Information Credibility Assessment"],"prefix":"10.1145","volume":"6","author":[{"given":"Lu","family":"He","sequence":"first","affiliation":[{"name":"University of California, Irvine, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changyang","family":"He","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (Lecture Notes in Computer Science)","author":"Alves Jairo L.","unstructured":"Jairo L. 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