{"type":"ScholarlyArticle","title":"Why Rumors Spread Fast in Social Networks, and How to Stop It","authors":[{"name":"Ahad N. Zehmakan","slug":"ahad-n-zehmakan","given":"Ahad","family":"N. Zehmakan","affiliation":"School of Computing , The Australian National University"},{"name":"Charlotte Out","slug":"charlotte-out","given":"Charlotte","family":"Out","affiliation":"Department of Computer Science & Technology , University of Cambridge"},{"name":"Sajjad Hesamipour Khelejan","slug":"sajjad-hesamipour-khelejan","given":"Sajjad","family":"Hesamipour Khelejan","affiliation":"School of Computer Science & Statistics , Trinity College Dublin"}],"abstract":"We study a rumor spreading model where individuals are connected via a network structure. Initially, only a small subset of the individuals are spreading a rumor. Each individual who is connected to a spreader, starts spreading the rumor with some probability as a function of their trust in the spreader, quantified by the Jaccard similarity index. Furthermore, the probability that a spreader diffuses the rumor decreases over time until they fully lose their interest and stop spreading.\r\n\r\nWe focus on determining the graph parameters which govern the magnitude and pace that the rumor spreads in this model. We prove that for the rumor to spread to a sizable fraction of the individuals, the network needs to enjoy ``strong'' expansion properties and most nodes should be in ``well-connected'' communities. Both of these characteristics are, arguably, present in real-world social networks up to a certain degree, shedding light on the driving force behind the extremely fast spread of rumors in social networks.\r\n\r\nFurthermore, we formulate a large range of countermeasures to cease the spread of a rumor. We introduce four fundamental criteria which a countermeasure ideally should possess. We evaluate all the proposed countermeasures by conducting experiments on real-world social networks such as Facebook and Twitter. We conclude that our novel decentralized countermeasures (which are executed by the individuals) generally outperform the previously studied centralized ones (which need to be imposed by a third entity such as the government).","doi":"10.24963/ijcai.2023/27","url":"https://ijcai.org/proceedings/2023/27","pdf":"https://ijcai.org/proceedings/2023/0027.pdf","markdown":"https://ijcai.org/proceedings/2023/27.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/27","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":27,"pages":{"first":234,"last":242},"keywords":["Agent-based and Multi-agent Systems: MAS: Agent theories and models","Multidisciplinary Topics and Applications: MDA: Web and social networks","Game Theory and Economic Paradigms: GTEP: Computational social choice"],"videos":[],"references":[{"position":1,"raw":"[Blondel et al., 2008] Vincent D Blondel, Jean-Loup Guil- laume, Renaud Lambiotte, and Etienne Lefebvre. 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