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Comput."],"published-print":{"date-parts":[[2019,9,30]]},"abstract":"<jats:p>Online discussions help individuals to gather knowledge and make important decisions in diverse areas from health and finance to computing and data science. Online discussion groups exhibit unique group dynamics not found in traditional small groups, such as staggered participation and asynchronous communication, and the effects of these features on knowledge sharing is not well understood. In this article, we focus on one such aspect: wide variation in group size. Using a controlled experiment with a hidden profile task, we evaluate online discussion groups\u2019 capacity to share distributed knowledge when group size ranges from 4 to 32 participants. We found that individuals in medium-sized discussions performed the best, and we suggest that this represents a tradeoff in which larger groups tend to share more facts, but have more difficulty than smaller groups at resolving misunderstandings.<\/jats:p>","DOI":"10.1145\/3359758","type":"journal-article","created":{"date-parts":[[2019,11,14]],"date-time":"2019-11-14T22:07:36Z","timestamp":1573769256000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["The Impact of Group Size on the Discovery of Hidden Profiles in Online Discussion Groups"],"prefix":"10.1145","volume":"2","author":[{"given":"Yla","family":"Tausczik","sequence":"first","affiliation":[{"name":"University of Maryland, MD, USA"}]},{"given":"Xiaoyun","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Maryland, MD, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,11,14]]},"reference":[{"volume-title":"Communities and Technologies","author":"Ackerman Mark S.","key":"e_1_2_1_1_1","unstructured":"Mark S. 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