Open AccessContainment of rumor spread by selecting immune nodes in social networks
Author(s) -
Hong Wu,
Zhijian Zhang,
Yabo Fang,
Shaotang Zhang,
Jiakuo Zuo,
Jian Huang,
Ping Li
Publication year - 2021
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2021133
Subject(s) - rumor , computer science , set (abstract data type) , popularity , social network (sociolinguistics) , containment (computer programming) , theoretical computer science , social media , world wide web , psychology , political science , social psychology , public relations , programming language
With the popularity of online social network these have become important platforms for the spread of information. This not only includes correct and useful information, but also false information, and even rumors which could result in panic. Therefore, the containment of rumor spread in social networks is important. In this paper, we propose an effective method that involves selecting a set of nodes in (k, η)-cores and immunize these nodes for rumor containment. First, we study rumor influence propagation in social networks under the extended Independent Cascade (EIC) model, an extension of the classic Independent Cascade (IC) model. Then, we decompose a social network into subgraphs via core decomposition of uncertain graphs and compute the number of immune nodes in each subgraph. Further we greedily select nodes with the Maximum Marginal Covering Neighbors Set as immune nodes. Finally, we conduct experiments using real-world datasets to evaluate our method. Experimental results show the effectiveness of our method.