进化博弈视角下考虑双重社会强化效应的多信息扩散模型研究

IF 3.5 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2024-12-24 DOI:10.1016/j.amc.2024.129255
Yuanyuan Ma , Qiannan Zhang , Leilei Xie
{"title":"进化博弈视角下考虑双重社会强化效应的多信息扩散模型研究","authors":"Yuanyuan Ma ,&nbsp;Qiannan Zhang ,&nbsp;Leilei Xie","doi":"10.1016/j.amc.2024.129255","DOIUrl":null,"url":null,"abstract":"<div><div>The dynamic interactions of multi-information in online social networks present new challenges for understanding and forecasting information dissemination trends, especially the bounded rational decision-making of users when faced with various information. This article introduces evolutionary game theory to analyze user strategies amidst varying information. By using the Fermi function to calculate the imitation probability of netizens and considering the attractiveness of information and the dual social reinforcement effect, a class of G-SF<sub>D</sub>F<sub>R</sub>R multi-information delay propagation models has been established. The propagation threshold is calculated using the next-generation matrix method, and the global asymptotic stability of the system is analyzed using the time-delay Lyapunov function. Empirical analysis based on a Twitter dataset validated the model's effectiveness, showing an improvement in the fitting degree of 38.91 and 19.21 % over the SCIR and SICMR models, respectively. Further quantitative analysis through numerical calculations revealed that evolutionary games can delay the peak of information dissemination and accelerate the decline of rumors, highlighting the key role of strategic interaction in curbing rumor spread. Additionally, regulating the positive and negative social reinforcement effects and propagation probabilities can optimize the effect of rumor refutation, with short-term forced silence measures being more effective than long-term ones.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"492 ","pages":"Article 129255"},"PeriodicalIF":3.5000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A study on multi-information diffusion model considering dual social reinforcement effect from the perspective of evolutionary game\",\"authors\":\"Yuanyuan Ma ,&nbsp;Qiannan Zhang ,&nbsp;Leilei Xie\",\"doi\":\"10.1016/j.amc.2024.129255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The dynamic interactions of multi-information in online social networks present new challenges for understanding and forecasting information dissemination trends, especially the bounded rational decision-making of users when faced with various information. This article introduces evolutionary game theory to analyze user strategies amidst varying information. By using the Fermi function to calculate the imitation probability of netizens and considering the attractiveness of information and the dual social reinforcement effect, a class of G-SF<sub>D</sub>F<sub>R</sub>R multi-information delay propagation models has been established. The propagation threshold is calculated using the next-generation matrix method, and the global asymptotic stability of the system is analyzed using the time-delay Lyapunov function. Empirical analysis based on a Twitter dataset validated the model's effectiveness, showing an improvement in the fitting degree of 38.91 and 19.21 % over the SCIR and SICMR models, respectively. Further quantitative analysis through numerical calculations revealed that evolutionary games can delay the peak of information dissemination and accelerate the decline of rumors, highlighting the key role of strategic interaction in curbing rumor spread. Additionally, regulating the positive and negative social reinforcement effects and propagation probabilities can optimize the effect of rumor refutation, with short-term forced silence measures being more effective than long-term ones.</div></div>\",\"PeriodicalId\":55496,\"journal\":{\"name\":\"Applied Mathematics and Computation\",\"volume\":\"492 \",\"pages\":\"Article 129255\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Mathematics and Computation\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0096300324007161\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300324007161","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0

摘要

在线社交网络中多种信息的动态交互对信息传播趋势的理解和预测提出了新的挑战,特别是用户面对多种信息时的有限理性决策。本文引入进化博弈论来分析用户在不同信息下的策略。利用费米函数计算网民的模仿概率,考虑信息的吸引力和双重社会强化效应,建立了一类G-SFDFRR多信息延迟传播模型。采用新一代矩阵法计算了传播阈值,并利用时滞Lyapunov函数分析了系统的全局渐近稳定性。基于Twitter数据集的实证分析验证了该模型的有效性,与SCIR和SICMR模型相比,拟合程度分别提高了38.91%和19.21%。进一步通过数值计算进行定量分析,发现进化博弈可以延缓信息传播的高峰,加速谣言的衰落,凸显了战略互动在遏制谣言传播中的关键作用。此外,调节正、负社会强化效应和传播概率可以优化辟谣效果,短期强制沉默措施比长期强制沉默措施更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A study on multi-information diffusion model considering dual social reinforcement effect from the perspective of evolutionary game
The dynamic interactions of multi-information in online social networks present new challenges for understanding and forecasting information dissemination trends, especially the bounded rational decision-making of users when faced with various information. This article introduces evolutionary game theory to analyze user strategies amidst varying information. By using the Fermi function to calculate the imitation probability of netizens and considering the attractiveness of information and the dual social reinforcement effect, a class of G-SFDFRR multi-information delay propagation models has been established. The propagation threshold is calculated using the next-generation matrix method, and the global asymptotic stability of the system is analyzed using the time-delay Lyapunov function. Empirical analysis based on a Twitter dataset validated the model's effectiveness, showing an improvement in the fitting degree of 38.91 and 19.21 % over the SCIR and SICMR models, respectively. Further quantitative analysis through numerical calculations revealed that evolutionary games can delay the peak of information dissemination and accelerate the decline of rumors, highlighting the key role of strategic interaction in curbing rumor spread. Additionally, regulating the positive and negative social reinforcement effects and propagation probabilities can optimize the effect of rumor refutation, with short-term forced silence measures being more effective than long-term ones.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
相关文献
二甲双胍通过HDAC6和FoxO3a转录调控肌肉生长抑制素诱导肌肉萎缩
IF 8.9 1区 医学Journal of Cachexia, Sarcopenia and MusclePub Date : 2021-11-02 DOI: 10.1002/jcsm.12833
Min Ju Kang, Ji Wook Moon, Jung Ok Lee, Ji Hae Kim, Eun Jeong Jung, Su Jin Kim, Joo Yeon Oh, Sang Woo Wu, Pu Reum Lee, Sun Hwa Park, Hyeon Soo Kim
具有疾病敏感单倍型的非亲属供体脐带血移植后的1型糖尿病
IF 3.2 3区 医学Journal of Diabetes InvestigationPub Date : 2022-11-02 DOI: 10.1111/jdi.13939
Kensuke Matsumoto, Taisuke Matsuyama, Ritsu Sumiyoshi, Matsuo Takuji, Tadashi Yamamoto, Ryosuke Shirasaki, Haruko Tashiro
封面:蛋白质组学分析确定IRSp53和fastin是PRV输出和直接细胞-细胞传播的关键
IF 3.4 4区 生物学ProteomicsPub Date : 2019-12-02 DOI: 10.1002/pmic.201970201
Fei-Long Yu, Huan Miao, Jinjin Xia, Fan Jia, Huadong Wang, Fuqiang Xu, Lin Guo
来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
期刊最新文献
Unsteady one dimensional motions of a new class of seemingly viscoplastic materials On controllability of fractional-order impulsive and switching systems with time delay Bifurcations analysis of a 3D Filippov pest-natural enemy system with stage structure for the prey Evolutionary games for cooperation in open data management Convergence of mass transfer particle tracking schemes for the simulation of advection-diffusion-reaction equations
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1