{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:17:09Z","timestamp":1760710629032,"version":"3.41.2"},"reference-count":42,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T00:00:00Z","timestamp":1626134400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["INTR"],"published-print":{"date-parts":[[2022,3,15]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to achieve effective governance of online rumors through the proposed rumor propagation model and immunization strategy.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>The paper leverages the agent-based modeling (ABM) method to model individuals from two aspects, behavior and attitude. Based on the analysis and research of online data, we propose a rumor propagation model, namely the Untouched view transmit removed-Susceptible hesitate agree disagree (Unite-Shad), and devise an immunization strategy, namely the Gravity Immunization Strategy (GIS). A graph-based framework, namely Pregel, is used to carry out the rumor propagation simulation experiments. Through the experiments, the rationality of the Unite-Shad and the effectiveness of the GIS are verified.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The study discovers that the inconsistency between human behaviors and attitudes in rumor propagation can be explained by the Unite-shad model. Besides, the GIS, which shows better performance in small-world networks than in scale-free networks, can effectively suppress rumor propagation in the early stage.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title><jats:p>This paper provides an effective immunization strategy for rumor governance. Specifically, the Unite-Shad model reveals the mechanism of rumor propagation, and the GIS provides an effective governance method for selecting immune nodes.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The inconsistency of human behaviors and attitudes in real scenes is modeled in the Unite-Shad model. Combined with the model, the definition of diffusion domain is proposed and a novel immunization strategy, namely GIS, is designed, which is significant for the social governance of rumor propagation.<\/jats:p><\/jats:sec>","DOI":"10.1108\/intr-08-2020-0480","type":"journal-article","created":{"date-parts":[[2021,7,12]],"date-time":"2021-07-12T01:22:51Z","timestamp":1626052971000},"page":"620-639","source":"Crossref","is-referenced-by-count":8,"title":["The research on propagation modeling and governance strategies of online rumors based on behavior\u2013attitude"],"prefix":"10.1108","volume":"32","author":[{"given":"Hailiang","family":"Chen","sequence":"first","affiliation":[]},{"given":"Chuan","family":"Ai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2962-9254","authenticated-orcid":false,"given":"Bin","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yong","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Kaisheng","family":"Lai","sequence":"additional","affiliation":[]},{"given":"Lingnan","family":"He","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0659-1318","authenticated-orcid":false,"given":"Zhihan","family":"Liu","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"key2022031415450809400_ref001","unstructured":"Ahmad, O.B., Boschi-Pinto, C., Lopez, A., Murray, C.J.L., Lozano, R. and Inoue, M. 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