Abstract
In the recent years, information diffusion and strategy interaction on the multiplex networks have been greatly researched. Some significant progresses came at stochastic spreading models. However, the influences of individuals’ trust on strategy interaction and cooperation evolution were generally overlooked. Actually, in real social networks, the different trust levels of individuals are important factors in the information diffusion. Here, we will play some strategy games among individuals, as well as communities or groups in the weighted multiplex networks, to explore the effect of individuals’ trust on strategy interaction and cooperation evolution. Each individual uses a cache to storage certain length of previous strategy status, which indicates the individual’s trust degree on the strategy. When consecutive identical cooperation strategies occur in the individual’s cache, and exceed the certain threshold of strategy memory length, the cooperation strategy will be adopted in next interlayer and intralayer interactions, so as to explore community level diffusion. The results show that the individuals’ trust levels highly affect the strategy interaction and cooperation evolution in multiplex networks. The cache length of consecutive identical cooperation strategy is also the key parameter for information diffusion, and the tight degrees between different layers of networks together. This work will be helpful to understand cooperation dynamic and evolution in weighted multiplex networks.
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References
Buldyrev, S.V., Parshani, R., Paul, G., Stanley, H.E., Havlin, S.: Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010)
Wang, Z., Wang, L., Szolnoki, A., Perc, M.: Evolutionary games on multilayer networks: a colloquium. Eur. Phys. J. B 88, 124 (2015)
Liu, X., Stanley, H.E., Gao, J.: Breakdown of interdependent directed networks. Proc. Natl. Acad. Sci. USA 113(5), 1138–1143 (2016)
Santos, M.D., Dorogovtsev, S.N., Mendes, J.F.F.: Biased imitation in coupled evolutionary games in interdependent networks. Sci. Rep. 4, 4436 (2014)
Marialisa, S., et al.: Combining evolutionary game theory and network theory to analyze human cooperation patterns. Chaos Solitons Fractals 91, 17–24 (2019)
Wang, Z., Szolnoki, A., Perc, M.: Optimal interdependence between networks for the evolution of cooperation. Sci. Rep. 3, 2470 (2013)
Lugo, H., San Miguel, M.: Learning and coordinating in a multilayer network. Sci. Rep. 5, 7776 (2015)
Matamalas, J.T., Poncela-Casasnovas, J., Gómez, S., Arenas, A.: Strategical incoherence regulates cooperation in social dilemmas on multiplex networks. Sci. Rep. 5, 9519 (2015)
Luo, C., Zhang, X., Liu, H., Shao, R.: Cooperation in memory-based prisoner’s dilemma game on interdependent networks. Physica A 450, 560–569 (2016)
Huang, K., et al.: Understanding cooperative behavior based on the coevolution of game strategy and link weight. Sci. Rep. 5, 14783 (2015)
Centola, D.: The spread of behavior in an online social network experiment. Science 329, 1194–1196 (2010)
Santos, F.C., Pacheco, J.M.: Tom Lenaerts: evolutionary dynamics of social dilemmas in structured heterogeneous populations. Proc. Natl. Acad. Sci. USA 103(9), 3490–3494 (2006)
Watts, D.J.: A simple model of global cascades on random networks. Proc. Natl. Acad. Sci. USA 99(9), 5766–5771 (2002)
Weng, L., Menczer, F., Ahn, Y.-Y.: Virality prediction and community structure in social networks. Sci. Rep. 3, 2522 (2013)
Li, W., Tang, S., Fang, W., et al.: How multiple social networks affect user awareness: the information diffusion process in multiplex networks. Phys. Rev. E 92, 042810 (2019)
Wang, W., Liu, Q.H., Cai, S.M., et al.: Suppressing disease spreading by using information diffusion on multiplex networks. Sci. Rep. 6, 29259 (2016)
Wang, Z., Wang, L., Perc, M.: Degree mixing in multilayer networks impedes the evolution of cooperation. Phys. Rev. E 89(5), 052813 (2014)
Zhao, D., Wang, L., Li, S., Wang, Z., Wang, L., et al.: Immunization of epidemics in multiplex networks. PLoS ONE 9(11), e112018 (2018)
Liu, T., Li, P., Chen, Y., Zhang, J.: Community size effects on epidemic spreading in multiplex social networks. PLoS ONE 11(3), e0152021 (2016)
Emily, T.: Diffusion of innovations on community based Small Worlds: the role of correlation between social spheres. In: 15th Coalition Theory Network Workshop, Marseille, France (2010)
Rasoul, R., Mostafa, S., et al.: Diffusion of innovations over multiplex social networks. In: The International Symposium on Artificial Intelligence and Signal Processing (AISP), pp. 300–304. IEEE (2018)
Liu, Q.H., et al.: Impacts of complex behavioral responses on asymmetric interacting spreading dynamics in multiplex networks. Sci. Rep. 6, 25617 (2016)
Johan, U., Lars, B., Cameron, M., Jon, K.: Structural diversity in social contagion. Proc. Natl. Acad. Sci. USA 109(16), 5962–5966 (2012)
Michela, D.V., et al.: The spreading of misinformation online. Proc. Natl. Acad. Sci. USA 113(3), 554–559 (2016)
Azimi-Tafreshi, N.: Cooperative epidemics on multiplex networks. Phys. Rev. E 93(4), 042303 (2016)
Gabriel, E.K., Young, H.P.: Rapid innovation diffusion in social networks. Proc. Natl. Acad. Sci. USA 111(3), 10881–10888 (2014)
Kimura, M., Yamakawa, K., Saito, K., et al.: Community analysis of influential nodes for information diffusion on a social network. In: IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence),pp. 1358–1363. IEEE (2018)
Zang, W., Zhang, P., Zhou, C., Guo, L.: Discovering multiple diffusion source nodes in social networks. Procedia Comput. Sci. 29, 443–452 (2014)
Szolnoki, A., Perc, M.: Leaders should not be conformists in evolutionary social dilemmas. Sci. Rep 6, 23633 (2016)
Maksim, K., et al.: Identification of influential spreaders in complex networks. Nat. Phys. 6, 888–893 (2010)
Yu, J., Jiang, J.C., Xiang, L.: Group-based strategy diffusion in multiplex networks with weighted values. Physica A: Stat. Mech. Appl. 469, 148–156 (2017)
Axelrod, R., Hamilton, W.D.: The evolution of cooperation. Science 211, 1390–1396 (1981)
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This work was supported by The National Social Science Fund of China (No. 20BXW096).
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Yu, J., Luo, J., Li, P. (2021). Impacts of Individuals’ Trust in Information Diffusion of the Weighted Multiplex Networks. In: Sun, Y., Liu, D., Liao, H., Fan, H., Gao, L. (eds) Computer Supported Cooperative Work and Social Computing. ChineseCSCW 2020. Communications in Computer and Information Science, vol 1330. Springer, Singapore. https://doi.org/10.1007/978-981-16-2540-4_10
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DOI: https://doi.org/10.1007/978-981-16-2540-4_10
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