2012/08/30 by Anurag Singh, Yatindra Nath Singh · 49 citations
Computer Science · Mathematics · Physics and Astronomy · Psychology · #Combinatorics #Complex Network Analysis Techniques #Complex network #Computer science #Degree (music) #Exponent #Law #Mathematics #Mental Health Research Topics #Node (physics) #Nonlinear system #Opinion Dynamics and Social Influence #Physics #Rumor #Scale (ratio) #Scale-free network #Statistics #cs.SI #physics.soc-ph
paper · pdf · doi:10.5506/aphyspolb.44.5
published in Acta Physica Polonica B 44(1), 5 (Jagiellonian University) · 27 pages 15 figures
arxiv created 2012/08/30 · openalex publication_date 2013/01/01 · arxiv updated 2013/04/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In earlier rumor spreading models of the real world complex networks, nodes contact all of their neighbors at each time step. In more realistic scenario, a node may contact only some of its neighbors to spread the rumor. The rumor spreading rate may also depend on the degree of the spreader and ignorant nodes. We have given a new modified rumor spreading model to accommodate these facts. This new model has been studied for rumor spreading in scale free networks model of real world complex networks. Nonlinear rumor spread exponent and degree dependent tie strength exponent of nodes affect the rumor threshold. By using the given two exponents, rumor threshold has some finite value. This was not observed in the earlier models for scale free networks. The rumor threshold becomes independent of network size when and parameters are tuned to appropriate value. In any social network, rumors can spread and may have undesirable effect. One of the possible solutions to control rumor spread is to inoculate a certain fraction of nodes against rumors. We have used modified rumor spreading model over scale free networks to investigate the efficacy of random and targeted inoculation schemes. It has been observed that rumor threshold in targeted inoculation scheme is higher than in the random inoculation. Therefore, it is hard to spread rumors using modified rumor spreading model in scale free networks using targeted inoculation scheme. The proposed hypothesis is also verified by the simulation results.