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Interact."],"published-print":{"date-parts":[[2021,4,13]]},"abstract":"<jats:p>A growing number of people are using catch-up TV services rather than watching simultaneously with other audience members at the time of broadcast. However, computational support for such catching-up users has not been well explored. In particular, we are observing an emerging phenomenon in online media consumption experiences in which speculation plays a vital role. As the phenomenon of speculation implicitly assumes simultaneity in media consumption, there is a gap for catching-up users, who cannot directly appreciate the consumption experiences. This conversely suggests that there is potential for computational support to enhance the consumption experiences of catching-up users. Accordingly, we conducted a series of studies to pave the way for developing computational support for catching-up users. First, we conducted semi-structured interviews to understand how people are engaging with speculation during media consumption. As a result, we discovered the distinctive aspects of speculation-based consumption experiences in contrast to social viewing experiences sharing immediate reactions that have been discussed in previous studies. We then designed two prototypes for supporting catching-up users based on our quantitative analysis of Twitter data in regard to reaction- and speculation-based media consumption. Lastly, we evaluated the prototypes in a user experiment and, based on its results, discussed ways to empower catching-up users with computational supports in response to recent transformations in media consumption.<\/jats:p>","DOI":"10.1145\/3449225","type":"journal-article","created":{"date-parts":[[2021,4,22]],"date-time":"2021-04-22T17:49:24Z","timestamp":1619113764000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Reaction or Speculation: Building Computational Support for Users in Catching-Up Series Based on an Emerging Media Consumption Phenomenon"],"prefix":"10.1145","volume":"5","author":[{"given":"Riku","family":"Arakawa","sequence":"first","affiliation":[{"name":"The University of Tokyo, Hongo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiromu","family":"Yakura","sequence":"additional","affiliation":[{"name":"University of Tsukuba &amp; Teambox Inc., Tsukuba, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,4,22]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11235-016-0157-3"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10606-012-9165-3"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/meet.14505001073"},{"key":"e_1_2_1_4_1","first-page":"37","article-title":"#ausvotes: How Twitter Covered the 2010 Australian Federal Election","volume":"44","author":"Bruns Axel","year":"2011","unstructured":"Axel Bruns and Jean Burgess. 2011. #ausvotes: How Twitter Covered the 2010 Australian Federal Election. 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