Containment of rumor spread by selecting immune nodes in social networks
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 netwo...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2021-04-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | http://www.aimspress.com/article/doi/10.3934/mbe.2021133?viewType=HTML |
| _version_ | 1818675837346512896 |
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| author | Hong Wu Zhijian Zhang Yabo Fang Shaotang Zhang Zuo Jiang Jian Huang Ping Li |
| author_facet | Hong Wu Zhijian Zhang Yabo Fang Shaotang Zhang Zuo Jiang Jian Huang Ping Li |
| author_sort | Hong Wu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T08:33:55Z |
| format | Article |
| id | doaj.art-24e8aff8f47040a29a86824751baf164 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-12-17T08:33:55Z |
| publishDate | 2021-04-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-24e8aff8f47040a29a86824751baf1642022-12-21T21:56:32ZengAIMS PressMathematical Biosciences and Engineering1551-00182021-04-011832614263110.3934/mbe.2021133Containment of rumor spread by selecting immune nodes in social networksHong Wu0Zhijian Zhang1Yabo Fang 2Shaotang Zhang 3Zuo Jiang 4Jian Huang5Ping Li61. School of Information Engineering, Qujing Normal University, Qujing 655000, China2. Faculty of Science, Kunming University of Science and Technology, Kunming 650031, China2. Faculty of Science, Kunming University of Science and Technology, Kunming 650031, China 3. School of Mathematics, Jilin University, Changchun 130012, China1. School of Information Engineering, Qujing Normal University, Qujing 655000, China4. School of Mathematics & Computer Science, Yunnan Minzu University, Kunming 650031, China1. School of Information Engineering, Qujing Normal University, Qujing 655000, China1. School of Information Engineering, Qujing Normal University, Qujing 655000, ChinaWith 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.http://www.aimspress.com/article/doi/10.3934/mbe.2021133?viewType=HTMLsocial networkscontainment of rumor spread(kη) cores decompositionextended independent cascade modelgreedy algorithm |
| spellingShingle | 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 Mathematical Biosciences and Engineering social networks containment of rumor spread (k η) cores decomposition extended independent cascade model greedy algorithm |
| title | Containment of rumor spread by selecting immune nodes in social networks |
| title_full | Containment of rumor spread by selecting immune nodes in social networks |
| title_fullStr | Containment of rumor spread by selecting immune nodes in social networks |
| title_full_unstemmed | Containment of rumor spread by selecting immune nodes in social networks |
| title_short | Containment of rumor spread by selecting immune nodes in social networks |
| title_sort | containment of rumor spread by selecting immune nodes in social networks |
| topic | social networks containment of rumor spread (k η) cores decomposition extended independent cascade model greedy algorithm |
| url | http://www.aimspress.com/article/doi/10.3934/mbe.2021133?viewType=HTML |
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