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Soc. Comput."],"published-print":{"date-parts":[[2018,3,31]]},"abstract":"<jats:p>Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societal point of view but also allows the filtering and aggregation of social media content for disseminating news stories. In this article, we perform a systematic methodological study of controversy detection by using the content and the network structure of social media.<\/jats:p>\n          <jats:p>\n            Unlike previous work, rather than studying controversy in a single hand-picked topic and using domain-specific knowledge, we take a general approach to study topics\n            <jats:italic>in any domain<\/jats:italic>\n            . Our approach to quantifying controversy is based on a graph-based three-stage pipeline, which involves (i) building a\n            <jats:italic>conversation graph<\/jats:italic>\n            about a topic, (ii) partitioning the conversation graph to identify potential sides of the controversy, and (iii)\u00a0measuring the amount of controversy from characteristics of the graph.\n          <\/jats:p>\n          <jats:p>We perform an extensive comparison of controversy measures, different graph-building approaches, and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy and show that content features are vastly less helpful in this task.<\/jats:p>","DOI":"10.1145\/3140565","type":"journal-article","created":{"date-parts":[[2018,4,5]],"date-time":"2018-04-05T20:10:25Z","timestamp":1522959025000},"page":"1-27","source":"Crossref","is-referenced-by-count":235,"title":["Quantifying Controversy on Social Media"],"prefix":"10.1145","volume":"1","author":[{"given":"Kiran","family":"Garimella","sequence":"first","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Gianmarco De Francisci","family":"Morales","sequence":"additional","affiliation":[{"name":"Qatar Computing Research Institute, Doha, Qatar"}]},{"given":"Aristides","family":"Gionis","sequence":"additional","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Michael","family":"Mathioudakis","sequence":"additional","affiliation":[{"name":"CNRS LIRIS 8 INSA Lyon, Lyon, France"}]}],"member":"320","published-online":{"date-parts":[[2018,1,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1134271.1134277"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the International AAAI Conference on Web and Social Media (ICWSM\u201914)","author":"Akoglu Leman","year":"2014","unstructured":"Leman Akoglu . 2014 . 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