Opinion Dynamics And Communication Networks
Abstract
This paper examines the interplay of opinion exchange dynamics and communication network formation. An opinion formation procedure is introduced which is based on an abstract representation of opinions as k-dimensional bit-strings. Individuals interact if the difference in the opinion strings is below a defined similarity threshold dI. Depending on dI, different behavior of the population is observed: low values result in a state of highly fragmented opinions and higher values yield consensus. The first contribution of this research is to identify the values of parameters dI and k, such that the transition between fragmented opinions and homogeneity takes place. Then, we look at this transition from two perspectives: first by studying the group size distribution and second by analyzing the communication network that is formed by the interactions that take place during the simulation. The emerging networks are classified by statistical means and we find that nontrivial social structures emerge from simple rules for individual communication. Generating networks allows to compare model outcomes with real-world communication patterns.Download Info
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Bibliographic Info
Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal Advances in Complex Systems.
Volume (Year): 13 (2010)
Issue (Month): 01 ()
Pages: 95-111
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Web page: http://www.worldscinet.com/acs/acs.shtml
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Related research
Keywords: Opinion dynamics; social networks; co-evolution; computational models; artificial societies;Other versions of this item:
- Sven Banisch & Tanya Araujo & Jorge Louçã, 2009. "Opinion Dynamics and Communication Networks," Working Papers 2009/16, Department of Economics at the School of Economics and Management (ISEG), Technical University of Lisbon..
References
References listed on IDEASPlease report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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"Innovation Success and Structural Change: An Abstract Agent Based Study,"
Working Papers
2007/25, Department of Economics at the School of Economics and Management (ISEG), Technical University of Lisbon..
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Handbook of Computational Economics,
in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011
Elsevier.
- John Duffy, 2004. "Agent-Based Models and Human Subject Experiments," Computational Economics 0412001, EconWPA.
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