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Article: A Dissemination Model Based on Psychological Theories in Complex Social Networks

TitleA Dissemination Model Based on Psychological Theories in Complex Social Networks
Authors
KeywordsComplex networks
differential dissemination
dissemination mechanism
information dissemination
psychology
Issue Date2022
Citation
IEEE Transactions on Cognitive and Developmental Systems, 2022, v. 14, n. 2, p. 519-531 How to Cite?
AbstractInformation spread on social media has been extensively studied through both model-driven theoretical research and data-driven case studies. Recent empirical studies have analyzed the differences and complexity of information dissemination, but theoretical explanations of its characteristics from a modeling perspective are underresearched. To capture the complex patterns of the information dissemination mechanism, we propose a resistant linear threshold (RLT) dissemination model based on psychological theories and empirical findings. In this article, we validate the RLT model on three types of networks and then quantify and compare the dissemination characteristics of the simulation results with those from the empirical results. In addition, we examine the factors affecting dissemination. Finally, we perform two case studies of the 2019 novel Corona Virus Disease (COVID-19)-related information dissemination. The dissemination characteristics derived by the simulations are consistent with the empirical research. These results demonstrate that the RLT model is able to capture the patterns of information dissemination on social media and thus provide model-driven insights into the interpretation of public opinion, rumor control, and marketing strategies on social media.
Persistent Identifierhttp://hdl.handle.net/10722/330691
ISSN
2023 Impact Factor: 5.0
2023 SCImago Journal Rankings: 1.302
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLuo, Tianyi-
dc.contributor.authorCao, Zhidong-
dc.contributor.authorZeng, Daniel-
dc.contributor.authorZhang, Qingpeng-
dc.date.accessioned2023-09-05T12:13:17Z-
dc.date.available2023-09-05T12:13:17Z-
dc.date.issued2022-
dc.identifier.citationIEEE Transactions on Cognitive and Developmental Systems, 2022, v. 14, n. 2, p. 519-531-
dc.identifier.issn2379-8920-
dc.identifier.urihttp://hdl.handle.net/10722/330691-
dc.description.abstractInformation spread on social media has been extensively studied through both model-driven theoretical research and data-driven case studies. Recent empirical studies have analyzed the differences and complexity of information dissemination, but theoretical explanations of its characteristics from a modeling perspective are underresearched. To capture the complex patterns of the information dissemination mechanism, we propose a resistant linear threshold (RLT) dissemination model based on psychological theories and empirical findings. In this article, we validate the RLT model on three types of networks and then quantify and compare the dissemination characteristics of the simulation results with those from the empirical results. In addition, we examine the factors affecting dissemination. Finally, we perform two case studies of the 2019 novel Corona Virus Disease (COVID-19)-related information dissemination. The dissemination characteristics derived by the simulations are consistent with the empirical research. These results demonstrate that the RLT model is able to capture the patterns of information dissemination on social media and thus provide model-driven insights into the interpretation of public opinion, rumor control, and marketing strategies on social media.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Cognitive and Developmental Systems-
dc.subjectComplex networks-
dc.subjectdifferential dissemination-
dc.subjectdissemination mechanism-
dc.subjectinformation dissemination-
dc.subjectpsychology-
dc.titleA Dissemination Model Based on Psychological Theories in Complex Social Networks-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCDS.2021.3052824-
dc.identifier.scopuseid_2-s2.0-85099727663-
dc.identifier.volume14-
dc.identifier.issue2-
dc.identifier.spage519-
dc.identifier.epage531-
dc.identifier.eissn2379-8939-
dc.identifier.isiWOS:000809402600027-

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