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Complex Systems and Complexity Science >

2015 , Vol. 12 >Issue 3: 45 - 52

DOI: https://doi.org/10.13306/j.1672-3813.2015.03.008

The Research of Dynamic Rumor Spreading Model and Influential Nodes Based on Online Social Network

  • MENG Zaiqiao ,
  • FU Xiufen ,
  • CHEN Peiwen ,
  • LU Jingqiao
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  • 1. School of Information Science and Technology, Sun Yat-sen University, Guangzhou 510006, China;
    2. School of Computer,Guangdong University of Technology, Guangzhou 510006, China

Received date: 2014-01-20

  Revised date: 2014-04-24

  Online published: 2026-06-22

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Abstract

Recent literature has revealed that the classical rumor spreading models were severely short when descripting the complex activity patterns of online social network (OSN). In this paper, we proposed a new dynamic rumor spreading model (DRSIR) based on OSN. In this model, we introduced the time delay annihilation function of spreaders, the dynamic authority and resistance of nodes and the receiving reinforced signal mechanisms with the aim of filling the gap between theoretical and experimental results. We verified the effectiveness of the model by simulating rumor spreading on the real-world OSN which crawled from Sina microblog. To Identifying influential nodes in directed OSN, we used the DRSIR model to perform computer simulations by the initialization of every node to be the single spreader to examine the spreading influence of the nodes ranked by different centrality measures and find surprising results. Namely, the spreading capabilities of the nodes do not depend on their k-core index, which is obtained by successive pruning of nodes with degree, and instead, the outdegree and the closeness centrality of nodes seem to be the better topological descriptor to locate such influential individuals.

Key words： online social network; rumor spreading model; modeling and simulation; influential nodes

Cite this article

MENG Zaiqiao , FU Xiufen , CHEN Peiwen , LU Jingqiao . The Research of Dynamic Rumor Spreading Model and Influential Nodes Based on Online Social Network[J]. Complex Systems and Complexity Science, 2015 , 12(3) : 45 -52 . DOI: 10.13306/j.1672-3813.2015.03.008

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