{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T12:01:30Z","timestamp":1775044890103,"version":"3.50.1"},"reference-count":92,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2019,11,16]],"date-time":"2019-11-16T00:00:00Z","timestamp":1573862400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["J. Data and Information Quality"],"published-print":{"date-parts":[[2020,3,31]]},"abstract":"<jats:p>Governance of misinformation is a serious concern in social media platforms. Based on experiences gathered from different case studies, we offer insights for the policymakers on managing misinformation in social media. These platforms are widely used for not just communication but also content consumption. Managing misinformation is thus a challenge for policymakers and the platforms. This article explores the factors of rapid propagation of misinformation based on our experiences in the domain. An average of about 1.5 million tweets were analysed in each of the three different cases surrounding misinformation. The findings indicate that the tweet emotion and polarity plays a significant role in determining whether the shared content is authentic or not. A deeper exploration highlights that a higher element of surprise combined with other emotions is present in such tweets. Further, the tweets that show case-neutral content often lack the possibilities of virality when it comes to misinformation. The second case explores whether the misinformation is being propagated intentionally by means of the identified fake profiles or it is done by authentic users, which can also be either intentional, for gaining attention, or unintentional, under the assumption that the information is correct. Last, network attributes, including topological analysis, community, and centrality analysis, also catalyze the propagation of misinformation. Policymakers can utilize these findings in this experience study for the governance of misinformation. Tracking and disruption in any one of the identified drivers could act as a control mechanism to manage misinformation propagation.<\/jats:p>","DOI":"10.1145\/3341107","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T13:01:53Z","timestamp":1574082113000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":37,"title":["Experience"],"prefix":"10.1145","volume":"12","author":[{"given":"Reema","family":"Aswani","sequence":"first","affiliation":[{"name":"Indian Institute of Technology Delhi, Hauz Khas, New Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arpan Kumar","family":"Kar","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Delhi, Hauz Khas, New Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P. Vigneswara","family":"Ilavarasan","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology Delhi, Hauz Khas, New Delhi"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,11,16]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer","author":"Romero D. M."},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the IEEE 13th International Conference on Data Mining (ICDM\u201913)","author":"Kwon S."},{"key":"e_1_2_1_3_1","unstructured":"K. Hill. 2012. Hurricane Sandy @ComfortablySmug and the Flood of Social Media Misinformation. Retrieved from http:\/\/www.forbes.com\/sites\/kashmirhill\/2012\/10\/30\/hurricane-sandy-and-the-flood-of social-media-misinformation\/.  K. Hill. 2012. Hurricane Sandy @ComfortablySmug and the Flood of Social Media Misinformation. 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