Statistical Properties of Community Dynamics in Large Social Networks

  • Authors:

  • Gergely Palla;Tamás Vicsek

  • Affiliations:

  • Statistical and Biological Research Group of the Hungarian Academy of Sciences, Hungary;Statistical and Biological Research Group of the Hungarian Academy of Sciences and Eötvös University, Hungary

  • Venue:
  • International Journal of Agent Technologies and Systems
  • Year:
  • 2009

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Abstract

The authors' focus is on the general statistical features of the time evolution of communities (also called as modules, clusters or cohesive groups) in large social networks. These structural sub-units can correspond to highly connected circles of friends, families, or professional cliques, which are subject to constant change due to the intense fluctuations in the activity and communication patterns of people. The communities can grow by recruiting new members, or contract by loosing members; two (or more) groups may merge into a single community, while a large enough social group can split into several smaller ones; new communities are born and old ones may disappear. According to our results, the time evolution of social groups containing only a few members and larger communities, e.g., institutions show significant differences.