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However, networkbased clues revealed when analyzing news propagation on social networks is an information that has hardly been comprehensively explored or used for fake news detection. We bridge this gap by proposing a network-based pattern-driven fake news detection approach. We aim to study the patterns of fake news in social networks, which refer to the news being spread, spreaders of the news and relationships among the spreaders. Empirical evidence and interpretations on the existence of such patterns are provided based on social psychological theories. These patterns are then represented at various network levels (i.e., node-level, ego-level, triad-level, community-level and the overall network) for being further utilized to detect fake news. The proposed approach enhances the explainability in fake news feature engineering. Experiments conducted on real-world data demonstrate that the proposed approach can outperform the state of the arts.<\/jats:p>","DOI":"10.1145\/3373464.3373473","type":"journal-article","created":{"date-parts":[[2019,11,27]],"date-time":"2019-11-27T08:21:28Z","timestamp":1574842888000},"page":"48-60","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":178,"title":["Network-based Fake News Detection"],"prefix":"10.1145","volume":"21","author":[{"given":"Xinyi","family":"Zhou","sequence":"first","affiliation":[{"name":"Syracuse University, Syracuse, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reza","family":"Zafarani","sequence":"additional","affiliation":[{"name":"Syracuse University, Syracuse, NY, 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":"10.1088\/1742-5468\/2008\/10\/P10008"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1245200"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963500"},{"key":"e_1_2_1_4_1","unstructured":"R. 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