Weimin Li, Dingmei Wei, Xiaokang Zhou, Shaohua Li, Qun Jin
{"title":"F - SWIR:考虑融合信息衰减的谣言传播模型","authors":"Weimin Li, Dingmei Wei, Xiaokang Zhou, Shaohua Li, Qun Jin","doi":"10.1002/cpe.7166","DOIUrl":null,"url":null,"abstract":"The spread of rumors has a major negative impact on social stability. Traditional rumor spreading models are mostly based on infectious disease models and do not consider the influence of individual differences and the network structure on rumor spreading. In this paper, we propose a rumor Fick‐spreading model that integrates information decay in social networks. The dissemination of rumors in social networks is random and uncertain and is affected by the dissemination capabilities of individuals and the network environment. The rumor Fick‐transition coefficient and Fick‐transition gradient are defined to determine the influence of the individual transition capacity and the network environment on rumor propagation, respectively. The Fick‐state transition probability is used to describe the probability of change of an individual's state. Moreover, an information decay function is defined to characterize the self‐healing probability of individuals. According to the different roles and reactions of users during rumor dissemination, the user state and the rumor dissemination rules among users are refined, and the influence of the network structure on the rumor dissemination is ascertained. The experimental results demonstrate that the proposed model outperforms other rumor spread models.","PeriodicalId":10584,"journal":{"name":"Concurrency and Computation: Practice and Experience","volume":"35 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"F‐SWIR: Rumor Fick‐spreading model considering fusion information decay in social networks\",\"authors\":\"Weimin Li, Dingmei Wei, Xiaokang Zhou, Shaohua Li, Qun Jin\",\"doi\":\"10.1002/cpe.7166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The spread of rumors has a major negative impact on social stability. Traditional rumor spreading models are mostly based on infectious disease models and do not consider the influence of individual differences and the network structure on rumor spreading. In this paper, we propose a rumor Fick‐spreading model that integrates information decay in social networks. The dissemination of rumors in social networks is random and uncertain and is affected by the dissemination capabilities of individuals and the network environment. The rumor Fick‐transition coefficient and Fick‐transition gradient are defined to determine the influence of the individual transition capacity and the network environment on rumor propagation, respectively. The Fick‐state transition probability is used to describe the probability of change of an individual's state. Moreover, an information decay function is defined to characterize the self‐healing probability of individuals. According to the different roles and reactions of users during rumor dissemination, the user state and the rumor dissemination rules among users are refined, and the influence of the network structure on the rumor dissemination is ascertained. The experimental results demonstrate that the proposed model outperforms other rumor spread models.\",\"PeriodicalId\":10584,\"journal\":{\"name\":\"Concurrency and Computation: Practice and Experience\",\"volume\":\"35 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Concurrency and Computation: Practice and Experience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/cpe.7166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrency and Computation: Practice and Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/cpe.7166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
F‐SWIR: Rumor Fick‐spreading model considering fusion information decay in social networks
The spread of rumors has a major negative impact on social stability. Traditional rumor spreading models are mostly based on infectious disease models and do not consider the influence of individual differences and the network structure on rumor spreading. In this paper, we propose a rumor Fick‐spreading model that integrates information decay in social networks. The dissemination of rumors in social networks is random and uncertain and is affected by the dissemination capabilities of individuals and the network environment. The rumor Fick‐transition coefficient and Fick‐transition gradient are defined to determine the influence of the individual transition capacity and the network environment on rumor propagation, respectively. The Fick‐state transition probability is used to describe the probability of change of an individual's state. Moreover, an information decay function is defined to characterize the self‐healing probability of individuals. According to the different roles and reactions of users during rumor dissemination, the user state and the rumor dissemination rules among users are refined, and the influence of the network structure on the rumor dissemination is ascertained. The experimental results demonstrate that the proposed model outperforms other rumor spread models.