Extremism propagation in social networks with hubs

Adaptive Behavior

Volumn 16, Issue 4, 2008, Pages 264-274

  Franks, Daniel W ^a   Noble, Jason ^b   Kaufmann, Peter ^c   Stagl, Sigrid ^c  

^a UNIVERSITY OF YORK   (United Kingdom)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^c UNIVERSITY OF SUSSEX   (United Kingdom)

Author keywords

Extremism; Opinion change; Scale free; Small world; Social networks

Indexed keywords

EID: 48349116091     PISSN: 10597123     EISSN: 17412633     Source Type: Journal    
DOI: 10.1177/1059712308090536     Document Type: Article

References (22)

1. Amblard, F., & Deffuant, G. (2004). The role of network topology on extremism propagation with the relative agreement opinion dynamics. Physica A, 343, 725-738.
2. Axelrod, R. (1986). An evolutionary approach to norms. American Political Science Review, 80, 1095-1111.
3. Barabsi, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286, 509-512.
4. Boyd, R., & Richerson, P.J. (1985). Culture and the evolutionary process. Chicago, IL: Chicago University Press.
5. Deffuant, G. (2006). Comparing extremism propagation patterns in continuous opinion models. Journal of Artificial Societies and Social Simulation, 9 (3). 8.
6. Deffuant, G., Amblard, F., Weisbuch, G., & Faure, T. (2002). How can extremism prevail? A study based on the relative agreement interaction model. Journal of Artificial Societies and Social Simulation, 5 (4). 1.
7. Dittmer, J.C. (2001). Consensus formation under bounded confidence. Nonlinear Analysis, 47, 4615-4621.
8. Kacpersky, K., & Holyst, J. (2000). Phase transition as a persistent feature of groups with leaders in models of opinion formation. Physica A, 287, 631-643.
9. Krause, U. (2000). A discrete nonlinear and non-autonomous model of consensus formation. In S. Elaydi, G. Ladas, J.Popenda, & J. Rakowski (Eds.), Communications in difference equations (pp. 227-236). London: Gordon and Breach.
10. Latan, B., & Nowak, A. (1997). Self-organizing social systems: Necessary and sufficient conditions for the emergence of clustering, consolidation, and continuing diversity. In G. A. Barnett & F. J. Boster (Eds.), Progress in communication sciences (pp. 1-24). Stamford, CT: Ablex Publishing Corporation.
11. Moscovici, S., & Lcuyer, R. (1972). Studies on polarization of judgments. European Journal of Social Psychology, 2, 221-244.
12. Newman, M.E.J. (2003). The structure and function of complex networks. SIAM Review, 45, 167-256.
13. Newman, M.E.J., & Park, J. (2003). Why social networks are different from other types of networks. Physical Review E, 68 (3). 03612 2.
14. Noble, J., Davy, S., & Franks, D.W. (2004). Effects of the topology of social networks on information transmission. In S. Schaal et al. (Eds.), From Animals to Animats 8: Proceedings of the 8th International Conference on Simulation of Adaptive Behavior (pp. 395-404). Cambridge, MA: MIT Press.
15. Noble, J., & Franks, D.W. (2004) Social learning in a multi-agent system. Computing and Informatics, 22 (6). 561-574.
16. Rogers, E.M. (1995). Diffusion of innovations, 4 th ed. New York: Free Press.
17. Salzarulo, L. (2006). A continuous opinion dynamics model based on the principle of meta-contrast. Journal of Artificial Societies and Social Simulation, 9 (1). 13.
18. Schelling, T. (1978). Micromotives and macro-behavior. New York: Norton.
19. Valente, T. (1995). Network models of the diffusion of innovations. Cresskill, NJ: Hampton Press.
20. Watts, D.J., & Strogatz, S.H. (1998). Collective dynamics of "small-world" networks. Nature, 393, 440-442.
21. Weisbuch, G., Deffuant, G., & Amblard, F. (2005). Persuasion dynamics. Physica A, 353, 555-575.
22. Wood, W. (2000). Attitude change: Persuasion and social influence. Annual Review of Psychology, 51, 539-570.