Abstract
Many studies show that social influences promote group polarization. In this paper we investigate the microscopic social mechanisms through agents based modeling and empirical data analysis. Both suggest that three types of social influences give rise to the emergence of macroscopic polarization, and the polarization pattern is closely link with local structure balance.
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Notes
- 1.
Holland and Leinhardt (1970) addressed that classic balance theory offers a set of simple local rules for relational change and classified local triadic motifs into 16 types, according to mutual reciprocity, asymmetry relation, non-relationship between pairs (or dyadic relations), where Code 300 triad relation corresponding to structure balance under the condition of the triad product signs satisfies “+”. More detail about structure balance please refer to [10–12].
References
Li, Z., Tang, X.: Polarization and non-positive social influence: a hopfield model of emergent structure. IJKSS 3(3), 15–25 (2012)
Li, Z., Tang, X.: Group polarization: connecting, influence and balance, a simulation study based on hopfield modeling. PRICAI 2012, 710–721 (2012)
Li, Z., Tang, X.: Group polarization and non-positive social influence: a revised voter model study. Brain Inform. 2011, 295–303 (2011)
Watts, D.J., Strogatz, S.: Collective dynamics of “small-world” networks. Nature 393(6684), 440–442 (1998)
Clifford, P., Sudbury, A.: A model for spatial conflict. Biometrika 60(3), 581–588 (1973)
Holley, R., Liggett, T.,: Ergodic theorems for weakly interacting infinite systems and the voter model. Ann. Probab. 3(4), 643–663 (1975)
Castellano, C., Vilone, D., Vespignani, A.: Incomplete Ordering of the voter model on Small-World Networks. EuroPhys. Lett. 63(1), 153–158 (2003)
Macy M,W., Kitts, J.A., Flache, A.: Polarization in dynamic networks a hopfield model of emergent structure. In: Breiger, R., Carley, K., Pattison, P. (eds.) Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, pp. 162–173. The National Academies Press, Washington (2003)
Butts, C.T.: Social Network Analysis with sna. J. Stat. Softw. 24(6), 1–51(2008)
Heider, F.: Attitudes and cognitive organization. J. Psychol. 21, 107–112 (1946)
Holland, P.W., Leinhardt, S.: A method for detecting structure in sociometric data. Am. J. Sociol. 70, 492–513 (1970)
Cartwright, D., Harary, F.: Structural balance: a generalization of Heider’s theory. Psychol. Rev. 63, 277–292 (1956)
Adamic, L., Glance, N.: The political blogosphere and the 2004 U.S. election: Divided they blog. In: Proc. 3rd Intl. Workshop on Link Discovery (LinkKDD), pp. 36–43 (2005)
Hargittai, E., Gallo, J., Kane, M.: Cross ideological discussions among con-servative and liberal bloggers. Public Choice 134(1), 67–86 (2007)
Conover, M.D., et al.: Political polarization on twitter. In: Proceedings of the 5th International Conference on Webblogs and Social Media, pp. 237–288, Barcelona (2011)
Acknowledgements
This research was supported by National Basic Research Program of China under Grant No. 2010CB731405, National Natural Science Foundation of China under Grant No.71171187.
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Li, Z., Tang, X. (2015). From Global Polarization to Local Social Mechanisms: A Study Based on ABM and Empirical Data Analysis. In: Bai, Q., Ren, F., Zhang, M., Ito, T., Tang, X. (eds) Smart Modeling and Simulation for Complex Systems. Studies in Computational Intelligence, vol 564. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55209-3_3
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