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Opinion formation in a social network: The role of human activity

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  • Grabowski, Andrzej

Abstract

The model of opinion formation in human population based on social impact theory is investigated numerically. On the basis of a database received from the on-line game server, we examine the structure of social network and human dynamics. We calculate the activity of individuals, i.e. the relative time devoted daily to interactions with others in the artificial society. We study the influence of correlation between the activity of an individual and its connectivity on the process of opinion formation. We find that such correlations have a significant influence on the temperature of the phase transition and the effect of the mass media, modeled as an external stimulation acting on the social network.

Suggested Citation

  • Grabowski, Andrzej, 2009. "Opinion formation in a social network: The role of human activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 961-966.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:6:p:961-966
    DOI: 10.1016/j.physa.2008.11.036
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    Cited by:

    1. Yang, Yan-Hong & Xie, Wen-Jie & Li, Ming-Xia & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2017. "Statistical properties of user activity fluctuations in virtual worlds," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 271-278.
    2. Laciana, Carlos E. & Rovere, Santiago L., 2011. "Ising-like agent-based technology diffusion model: Adoption patterns vs. seeding strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1139-1149.
    3. Sascha Holzhauer & Friedrich Krebs & Andreas Ernst, 2013. "Considering baseline homophily when generating spatial social networks for agent-based modelling," Computational and Mathematical Organization Theory, Springer, vol. 19(2), pages 128-150, June.
    4. Jiang, Zhi-Qiang & Ren, Fei & Gu, Gao-Feng & Tan, Qun-Zhao & Zhou, Wei-Xing, 2010. "Statistical properties of online avatar numbers in a massive multiplayer online role-playing game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 807-814.
    5. Carlos E. Laciana & Santiago L. Rovere, 2010. "Ising-like agent-based technology diffusion model: adoption patterns vs. seeding strategies," Papers 1011.3834, arXiv.org, revised Jan 2013.
    6. Liu, Ji & Deng, Guishi, 2009. "Link prediction in a user–object network based on time-weighted resource allocation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3643-3650.

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