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Impact of degree mixing pattern on consensus formation in social networks

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  • Liu, Xiao Fan
  • Tse, Chi Kong

Abstract

The consensus formation process in a social network is affected by a number of factors. This paper studies how the degree mixing pattern of a social network affects the consensus formation process. A social network of more than 50,000 nodes was sampled from the online social services website Twitter. Nodes in the Twitter user network are grouped by their in-degrees and out-degrees. A degree mixing correlation is proposed to measure the randomness of the mixing pattern for each degree group. The DeGroot model is used to simulate the consensus formation processes in the network. Simulation suggests that the non-random degree mixing pattern of social networks can slow down the rate of consensus.

Suggested Citation

  • Liu, Xiao Fan & Tse, Chi Kong, 2014. "Impact of degree mixing pattern on consensus formation in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 1-6.
    • Handle: RePEc:eee:phsmap:v:407:y:2014:i:c:p:1-6
    DOI: 10.1016/j.physa.2014.03.086
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    References listed on IDEAS

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    1. Yan, Qiang & Wu, Lianren & Zheng, Lan, 2013. "Social network based microblog user behavior analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1712-1723.
    2. Hollingshad, Nicholas W. & Svenkeson, Adam & West, Bruce J. & Grigolini, Paolo, 2013. "Time to consensus," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2302-2310.
    3. Pfau, Jens & Kirley, Michael & Kashima, Yoshihisa, 2013. "The co-evolution of cultures, social network communities, and agent locations in an extension of Axelrod’s model of cultural dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(2), pages 381-391.
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