{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T19:44:00Z","timestamp":1784835840259,"version":"3.55.0"},"reference-count":60,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2019,11,26]],"date-time":"2019-11-26T00:00:00Z","timestamp":1574726400000},"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":["SIGKDD Explor. Newsl."],"published-print":{"date-parts":[[2019,11,26]]},"abstract":"<jats:p>The widespread dissemination of misinformation in social media has recently received a lot of attention in academia. While the problem of misinformation in social media has been intensively studied, there are seemingly different definitions for the same problem, and inconsistent results in different studies. In this survey, we aim to consolidate the observations, and investigate how an optimal method can be selected given specific conditions and contexts. To this end, we first introduce a definition for misinformation in social media and we examine the difference between misinformation detection and classic supervised learning. Second, we describe the diffusion of misinformation and introduce how spreaders propagate misinformation in social networks. Third, we explain characteristics of individual methods of misinformation detection, and provide commentary on their advantages and pitfalls. By reflecting applicability of different methods, we hope to enable the intensive research in this area to be conveniently reused in real-world applications and open up potential directions for future studies.<\/jats:p>","DOI":"10.1145\/3373464.3373475","type":"journal-article","created":{"date-parts":[[2019,11,27]],"date-time":"2019-11-27T13:21:28Z","timestamp":1574860888000},"page":"80-90","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":351,"title":["Misinformation in Social Media"],"prefix":"10.1145","volume":"21","author":[{"given":"Liang","family":"Wu","sequence":"first","affiliation":[{"name":"Arizona State University, Tempe, AZ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fred","family":"Morstatter","sequence":"additional","affiliation":[{"name":"USC Information Sciences Institute, Marina Del Rey, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathleen M.","family":"Carley","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Liu","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, AZ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,11,26]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-014-0365-y"},{"key":"e_1_2_1_2_1","volume-title":"Measuring the impact of isis social media strategy","author":"Alfifi M.","year":"2018"},{"key":"e_1_2_1_3_1","first-page":"12","volume-title":"Collaboration, electronic messaging, anti-abuse and spam conference (CEAS)","author":"Benevenuto F.","year":"2010"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2133806.2133826"},{"key":"e_1_2_1_5_1","first-page":"667","volume-title":"ALIFE","author":"Bollen J.","year":"2010"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963500"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1108\/IntR-05-2012-0095"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1920261.1920265"},{"key":"e_1_2_1_9_1","volume-title":"ICWSM","author":"Friggeri A.","year":"2014"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835907"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2018.8508241"},{"key":"e_1_2_1_12_1","first-page":"2","volume-title":"Proceedings of the 1st workshop on privacy and security in online social media","author":"Gupta A."},{"key":"e_1_2_1_13_1","volume-title":"Unsupervised content-based identification of fake news articles with tensor decomposition ensembles","author":"Hosseinimotlagh S.","year":"2018"},{"key":"e_1_2_1_14_1","first-page":"2633","volume-title":"IJCAI","volume":"13","author":"Hu X.","year":"2013"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-60240-0_2"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159726"},{"key":"e_1_2_1_17_1","volume-title":"Homogeneity-based transmissive process to model true and false news in social networks. arXiv preprint arXiv:1811.09702","author":"Kim J.","year":"2018"},{"key":"e_1_2_1_18_1","first-page":"219","volume-title":"KDD","author":"Knorr E. 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