Affiliations: [a] School of Information Science and Engineering, Shandong Normal University, Jinan, China
| [b] School of Computer Science and Technology, Shandong Jianzhu University, Jinan, China
| [c] School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, China
| [d] Department of Computer and Information Engineering, Heze University, Heze, China
Correspondence:
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Corresponding author. Peiyu Liu, School of Information Science, and Engineering, Shandong Norma University, Jinan 250014, China. E-mail: yjzyj2006@163.com.
Abstract: In the study filed of rumor spreading, kill rumor or dispel rumor is very important in order to control rumor spreading and reduce the bad influence of the rumor. In the previous studies, rumor clarification is mostly finished by relying on external media or news reports instead of intervening and controlling from inside the network, which causes that the speed of rumor clarification is far lower than the speed of rumor spreading, and it is not ideal for the effect of rumor clarification. In this paper, a new Twin-SIR spreading model is proposed, in which, a rumor clarification node named as “rumor dispeller” with the spreading ability is introduced. The rumor dispeller is involved in the spreading process of the model together with the rumor spreader to control the spreading of rumor and thus to achieve the purpose of clarifying rumor. At the same time, during the process of building the model, we also apply the traditional media as a spreading parameter to the spreading process of the model. We built the mean-field equation of the model and then implemented further analysis of the model on homogeneous networks and heterogeneous networks. Through experimental simulations, the “rumor dispeller” was found to have the ability to reduce the spread of rumor spreading, and that the selection of the initial “rumor dispeller” node can affect the effect of rumor spreading, and at the same time, the external media have an important influence on rumor clarification. These conclusions have a new function for guiding us to study the mechanism of rumor spreading.
Keywords: Online social network, spreading model, rumor dispelling, twin-SIR model
