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Model for rumor spreading over networks
Open accessAbstract
An alternate model for rumor spreading over networks is suggested, in which two rumors (termed rumor 1 and rumor 2) with different probabilities of acceptance may propagate among nodes. The propagation is not symmetric in the sense that when deciding which rumor to adopt, nodes always consider rumor 1 first. The model is a natural generalization of the well-known epidemic SIS (susceptible-infective-susceptible) model and reduces to it when some of the parameters of this model are zero. We find that preferred rumor 1 is dominant in the network when the degree of nodes is high enough and/or when the network contains large clustered groups of nodes, expelling rumor 2. However, numerical simulations on synthetic networks show that it is possible for rumor 2 to occupy a nonzero fraction of the nodes in many cases as well. Specifically, in the Watts-Strogatz small-world model a moderate level of clustering supports its adoption, while increasing randomness reduces it. For Erdos-Renyi networks, a low average degree allows the coexistence of the two types of rumors. In Barabasi-Albert networks generated with a low m , where m is the number of links when a new node is added, it is also possible for rumor 2 to spread over the network.
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Cited by
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Vosoughi, S., Roy, D., & Aral, S. (2018) · Science · doi:10.1126/science.aap9559 · Cited by 8,847
Epidemic processes in complex networks
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.925 · Cited by 3,697
Dynamics of information diffusion and its applications on complex networks
Zhang, Z.-K., Liu, C., Zhan, X.-X., Lu, X., Zhang, C.-X., & Zhang, Y.-C. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.07.002 · Cited by 484
Influence Blocking Maximization in Social Networks under the Competitive Linear Threshold Model
He, X., Song, G., Chen, W., & Jiang, Q. (2012) · Proceedings of the 2012 SIAM International Conference on Data Mining · doi:10.1137/1.9781611972825.40 · Cited by 403
Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering
Chen, D.-B., Gao, H., Lü, L., & Zhou, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077455 · Cited by 364
Metadata
- Authors
- Trpevski, D., Tang, W. K. S., & Kocarev, L.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2010-05-04
- Volume
- 81
- Issue
- 5
- Pages
- 056102-056102
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W2040938924
- Cited by
- 215
- References
- 0
- FWCI
- 7.16
- Type
- journal article
- Language
- en
- Open access
- green
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