在社交网络中操纵意见

Manuel Mueller-Frank
{"title":"在社交网络中操纵意见","authors":"Manuel Mueller-Frank","doi":"10.2139/ssrn.3080219","DOIUrl":null,"url":null,"abstract":"We consider a general model of boundedly rational opinion formation in social networks. We show that long run opinions are extremely vulnerable to unilateral subtle manipulation. For a given updating system, any agent can drive the long run opinions of all agents to an arbitrary desired opinion, by infinitesimally perturbing his updating behavior. However, when opinion formation is monitored, then as the perturbation goes to zero so does the extend to which long run opinions can be manipulated without detection. Finally, we show that asymptotic consensus is a robust outcome of boundedly rational opinion formation while naive learning and social influence are not.","PeriodicalId":10477,"journal":{"name":"Cognitive Social Science eJournal","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Manipulating Opinions in Social Networks\",\"authors\":\"Manuel Mueller-Frank\",\"doi\":\"10.2139/ssrn.3080219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider a general model of boundedly rational opinion formation in social networks. We show that long run opinions are extremely vulnerable to unilateral subtle manipulation. For a given updating system, any agent can drive the long run opinions of all agents to an arbitrary desired opinion, by infinitesimally perturbing his updating behavior. However, when opinion formation is monitored, then as the perturbation goes to zero so does the extend to which long run opinions can be manipulated without detection. Finally, we show that asymptotic consensus is a robust outcome of boundedly rational opinion formation while naive learning and social influence are not.\",\"PeriodicalId\":10477,\"journal\":{\"name\":\"Cognitive Social Science eJournal\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Social Science eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3080219\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Social Science eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3080219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

我们考虑了社会网络中有限理性意见形成的一般模型。我们表明,长期的意见极易受到单方面的微妙操纵。对于给定的更新系统,任何智能体都可以通过无穷小地干扰其更新行为,将所有智能体的长期意见驱动为任意期望的意见。然而,当舆论形成受到监控时,随着扰动趋近于零,长期舆论被操纵而不被发现的程度也会趋近于零。最后,我们证明渐近共识是有限理性意见形成的稳健结果,而朴素学习和社会影响则不是。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Manipulating Opinions in Social Networks
We consider a general model of boundedly rational opinion formation in social networks. We show that long run opinions are extremely vulnerable to unilateral subtle manipulation. For a given updating system, any agent can drive the long run opinions of all agents to an arbitrary desired opinion, by infinitesimally perturbing his updating behavior. However, when opinion formation is monitored, then as the perturbation goes to zero so does the extend to which long run opinions can be manipulated without detection. Finally, we show that asymptotic consensus is a robust outcome of boundedly rational opinion formation while naive learning and social influence are not.
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
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信