Containment of rumor spread by selecting immune nodes in social networks

Hong Wu; Zhijian Zhang; Yabo Fang; Shaotang Zhang; Zuo Jiang; Jian Huang; Ping Li; Hong Wu; Zhijian Zhang; Yabo Fang; Shaotang Zhang; Zuo Jiang; Jian Huang; Ping Li

doi:10.3934/mbe.2021133

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 3: 2614-2631. doi: 10.3934/mbe.2021133

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Containment of rumor spread by selecting immune nodes in social networks

1.
School of Information Engineering, Qujing Normal University, Qujing 655000, China
2.
Faculty of Science, Kunming University of Science and Technology, Kunming 650031, China
3.
School of Mathematics, Jilin University, Changchun 130012, China
4.
School of Mathematics & Computer Science, Yunnan Minzu University, Kunming 650031, China

Received: 29 December 2020 Accepted: 23 February 2021 Published: 18 March 2021

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.
- social networks,
- containment of rumor spread,
- (k, η) cores decomposition,
- extended independent cascade model,
- greedy algorithm
Citation: Hong Wu, Zhijian Zhang, Yabo Fang, Shaotang Zhang, Zuo Jiang, Jian Huang, Ping Li. Containment of rumor spread by selecting immune nodes in social networks[J]. Mathematical Biosciences and Engineering, 2021, 18(3): 2614-2631. doi: 10.3934/mbe.2021133

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Abstract

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.

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