Abstract
We propose a method for identifying multiple influential spreaders in complex networks. This method is based on a farthest-first traversal of the network. The spreaders selected by this method satisfy the two criteria of being dispersed as well as influential in their neighborhood. To examine the influence of the spreaders identified by our method, we perform numerical simulations of SIR-based epidemic spread dynamics. For a range of parameter values, we observe that the epidemic size obtained using the spreaders generated by our method as the initial spreaders is at least as large as the epidemic size obtained using hubs as initial spreaders.
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References
Aral, S., Walker, D.: Identifying influential and susceptible members of social networks. Science 337(6092), 337–341 (2012)
Bao, Z.K., Liu, J.G., Zhang, H.F.: Identifying multiple influential spreaders by a heuristic clustering algorithm. Phys. Lett. A 381(11), 976–983 (2017)
Bonato, A., Janssen, J., Roshanbin, E.: Burning a graph as a model of social contagion. In: Bonato, A., Graham, F.C., Prałat, P. (eds.) WAW 2014. LNCS, vol. 8882, pp. 13–22. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-13123-8_2
Centola, D.: The spread of behavior in an online social network experiment. Science 329(5996), 1194–1197 (2010)
Da Silva, R.A.P., Viana, M.P., da Fontoura Costa, L.: Predicting epidemic outbreak from individual features of the spreaders. J. Stat. Mech. Theory Exp. 2012(07), P07005 (2012)
De Arruda, G.F., Barbieri, A.L., Rodríguez, P.M., Rodrigues, F.A., Moreno, Y., da Fontoura Costa, L.: Role of centrality for the identification of influential spreaders in complex networks. Phys. Rev. E 90(3), 032812 (2014)
De Arruda, G.F., Rodrigues, F.A., Moreno, Y.: Fundamentals of spreading processes in single and multilayer complex networks. Phys. Rep. 756, 1–59 (2018)
Gao, J., Barzel, B., Barabási, A.L.: Universal resilience patterns in complex networks. Nature 530(7590), 307–312 (2016)
Gao, J., Buldyrev, S.V., Havlin, S., Stanley, H.E.: Robustness of a network of networks. Phys. Rev. Lett. 107(19), 195701 (2011)
García-Díaz, J., Pérez-Sansalvador, J.C., Rodríguez-Henríquez, L.M.X., Cornejo-Acosta, J.A.: Burning graphs through farthest-first traversal. IEEE Access 10, 30395–30404 (2022)
Ghalmane, Z., El Hassouni, M., Cherifi, H.: Immunization of networks with non-overlapping community structure. Soc. Netw. Anal. Min. 9(1), 1–22 (2019)
He, J.L., Fu, Y., Chen, D.B.: A novel top-k strategy for influence maximization in complex networks with community structure. PloS one 10(12), e0145283 (2015)
Hu, Z.L., Liu, J.G., Yang, G.Y., Ren, Z.M.: Effects of the distance among multiple spreaders on the spreading. Europhys. Lett. 106(1), 18002 (2014)
Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. In: Proceedings of the ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 137–146 (2003)
Kitsak, M., et al.: Identification of influential spreaders in complex networks. Nat. Phys. 6(11), 888–893 (2010)
Lalou, M., Tahraoui, M.A., Kheddouci, H.: The critical node detection problem in networks: a survey. Comput. Sci. Rev. 28, 92–117 (2018)
Lü, L., Chen, D., Ren, X.L., Zhang, Q.M., Zhang, Y.C., Zhou, T.: Vital nodes identification in complex networks. Phys. Rep. 650, 1–63 (2016)
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., Vespignani, A.: Epidemic processes in complex networks. Rev. Mod. Phys. 87(3), 925 (2015)
Pastor-Satorras, R., Vespignani, A.: Immunization of complex networks. Phys. Rev. E 65(3), 036104 (2002)
Rosenkrantz, D.J., Stearns, R.E., Lewis, P.M., II.: An analysis of several heuristics for the traveling salesman problem. SIAM J. Comput. 6(3), 563–581 (1977)
Rossi, R.A., Ahmed, N.K.: The network data repository with interactive graph analytics and visualization. In: AAAI (2015). https://networkrepository.com
Shao, C., Ciampaglia, G.L., Varol, O., Yang, K.C., Flammini, A., Menczer, F.: The spread of low-credibility content by social bots. Nat. Commun. 9(1), 1–9 (2018)
Valente, T.W., Pumpuang, P.: Identifying opinion leaders to promote behavior change. Health Educ. Behav. 34(6), 881–896 (2007)
Wang, W., Liu, Q.H., Liang, J., Hu, Y., Zhou, T.: Coevolution spreading in complex networks. Phys. Rep. 820, 1–51 (2019)
Yanez-Sierra, J., Diaz-Perez, A., Sosa-Sosa, V.: An efficient partition-based approach to identify and scatter multiple relevant spreaders in complex networks. Entropy 23(9), 1216 (2021)
Zhang, D., Wang, Y., Zhang, Z.: Identifying and quantifying potential super-spreaders in social networks. Sci. Rep. 9(1), 14811 (2019)
Zhang, J.X., Chen, D.B., Dong, Q., Zhao, Z.D.: Identifying a set of influential spreaders in complex networks. Sci. Rep. 6(1), 27823 (2016)
Zhao, X.Y., Huang, B., Tang, M., Zhang, H.F., Chen, D.B.: Identifying effective multiple spreaders by coloring complex networks. Europhys. Lett. 108(6), 68005 (2015)
Zhao, Z., Wang, X., Zhang, W., Zhu, Z.: A community-based approach to identifying influential spreaders. Entropy 17(4), 2228–2252 (2015)
Zhou, M.Y., Xiong, W.M., Wu, X.Y., Zhang, Y.X., Liao, H.: Overlapping influence inspires the selection of multiple spreaders in complex networks. Phys. A 508, 76–83 (2018)
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Ramrakhiyani, M., Tiwari, M., Sunitha, V. (2024). Farthest-First Traversal for Identifying Multiple Influential Spreaders. In: Cherifi, H., Rocha, L.M., Cherifi, C., Donduran, M. (eds) Complex Networks & Their Applications XII. COMPLEX NETWORKS 2023. Studies in Computational Intelligence, vol 1142. Springer, Cham. https://doi.org/10.1007/978-3-031-53499-7_39
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