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Article: The impact of malicious nodes on the spreading of false information

TitleThe impact of malicious nodes on the spreading of false information
Authors
Issue Date2020
Citation
Chaos, 2020, v. 30, n. 8, article no. 083101 How to Cite?
AbstractIncreasing empirical evidence in recent years has shown that bots or malicious users in a social network play a critical role in the propagation of false information, while a theoretical modeling of such a problem has been largely ignored. In this paper, applying a simple contagion model, we study the effect of malicious nodes on the spreading of false information by incorporating the smart nodes who perform better than normal nodes in discerning false information. The malicious nodes, however, will always repost (or adopt) the false message as long as they receive it. We show analytically that, for a random distribution of malicious nodes, there is a critical number of malicious nodes above which the false information could outbreak in a random network. We further study three different distribution strategies of selecting malicious nodes for false information spreading. We find that malicious nodes that have large degrees, or are tightly connected, can enhance the spread. However, when they are close to the smart nodes, the spreading of false information can either be promoted or inhibited, depending on the network structure.
Persistent Identifierhttp://hdl.handle.net/10722/330652
ISSN
2023 Impact Factor: 2.7
2023 SCImago Journal Rankings: 0.778
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorRuan, Zhongyuan-
dc.contributor.authorYu, Bin-
dc.contributor.authorShu, Xincheng-
dc.contributor.authorZhang, Qingpeng-
dc.contributor.authorXuan, Qi-
dc.date.accessioned2023-09-05T12:12:48Z-
dc.date.available2023-09-05T12:12:48Z-
dc.date.issued2020-
dc.identifier.citationChaos, 2020, v. 30, n. 8, article no. 083101-
dc.identifier.issn1054-1500-
dc.identifier.urihttp://hdl.handle.net/10722/330652-
dc.description.abstractIncreasing empirical evidence in recent years has shown that bots or malicious users in a social network play a critical role in the propagation of false information, while a theoretical modeling of such a problem has been largely ignored. In this paper, applying a simple contagion model, we study the effect of malicious nodes on the spreading of false information by incorporating the smart nodes who perform better than normal nodes in discerning false information. The malicious nodes, however, will always repost (or adopt) the false message as long as they receive it. We show analytically that, for a random distribution of malicious nodes, there is a critical number of malicious nodes above which the false information could outbreak in a random network. We further study three different distribution strategies of selecting malicious nodes for false information spreading. We find that malicious nodes that have large degrees, or are tightly connected, can enhance the spread. However, when they are close to the smart nodes, the spreading of false information can either be promoted or inhibited, depending on the network structure.-
dc.languageeng-
dc.relation.ispartofChaos-
dc.titleThe impact of malicious nodes on the spreading of false information-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1063/5.0005105-
dc.identifier.pmid32872799-
dc.identifier.scopuseid_2-s2.0-85089438401-
dc.identifier.volume30-
dc.identifier.issue8-
dc.identifier.spagearticle no. 083101-
dc.identifier.epagearticle no. 083101-
dc.identifier.eissn1089-7682-
dc.identifier.isiWOS:000559328100001-

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