Impact of degree mixing pattern on consensus formation in social networks

Xiao Fan Liu, Chi Kong Tse

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Volume407
DOIs
Publication statusPublished - 1 Aug 2014

Keywords

  • Consensus
  • Degree mixing pattern
  • Social network
  • Twitter

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistics and Probability

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