A New Network Feature Affects the Intervention Performance on Public Opinion Dynamic Networks

doi:10.1038/s41598-019-41555-w

CORC > 数学与系统科学研究院 > 中国科学院数学与系统科学研究院 > 系统科学研究所

	A New Network Feature Affects the Intervention Performance on Public Opinion Dynamic Networks
	Wang, Caiyun 1,2; Han, Huawei 1; Han, Jing1,2
刊名	SCIENTIFIC REPORTS
	2019-03-25
卷号	9 页码:11
ISSN号	2045-2322
DOI	10.1038/s41598-019-41555-w
英文摘要	The neighborhood network structure plays an important role in the collective opinion of an opinion dynamic system. Does it also affect the intervention performance? To answer this question, we apply three intervention methods on an opinion dynamic model, the weighted DeGroot model, to change the convergent opinion value (x) over bar. And we define a new network feature Omega, called 'network differential degree', to measure how node degrees couple with influential values in the network, i.e., large Omega indicates nodes with high degree is more likely to couple with large influential value. We investigate the relationship between the intervention performance and the network differential degree Omega in the following three intervention cases: (1) add one special agent (shill) to connect to one normal agent; (2) add one edge between two normal agents; (3) add a number of edges among agents. Through simulations we find significant correlation between the intervention performance, i.e.,vertical bar(x) over barvertical bar (the maximum value of the change of convergent opinion value vertical bar(x) over bar vertical bar and Omega in all three cases: the intervention performance vertical bar( x) over barvertical bar is higher when Omega is smaller. So Omega could be used to predict how difficult it is to intervene and change the convergent opinion value of the weighted DeGroot model. Meanwhile, a theorem of adding one edge and an algorithm for adding optimal edges are given.
资助项目	National Natural Science Foundation of China[61374168] ; Frontier Science Key Programs of the Chinese Academy of Sciences[QYZDJ-SSW-JSC003]
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	NATURE PUBLISHING GROUP
WOS记录号	WOS:000462149800044
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/34309]
专题	系统科学研究所
通讯作者	Han, Jing
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Wang, Caiyun,Han, Huawei,Han, Jing. A New Network Feature Affects the Intervention Performance on Public Opinion Dynamic Networks[J]. SCIENTIFIC REPORTS,2019,9:11.
APA	Wang, Caiyun,Han, Huawei,&Han, Jing.(2019).A New Network Feature Affects the Intervention Performance on Public Opinion Dynamic Networks.SCIENTIFIC REPORTS,9,11.
MLA	Wang, Caiyun,et al."A New Network Feature Affects the Intervention Performance on Public Opinion Dynamic Networks".SCIENTIFIC REPORTS 9(2019):11.