Community dynamics in social networks

Gergely Palla*, Albert László Barabási, Tamas Vicsek

*Corresponding author for this work

Research output: Contribution to Book/Report typesConference contributionpeer-review

Abstract (may include machine translation)

We study the statistical properties of community dynamics in large social networks, where the evolving communities are obtained from subsequent snapshots of the modular structure. Such cohesive groups of people 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. We find significant difference between the behaviour of smaller collaborative or friendship circles and larger communities, eg. institutions. Social groups containing only a few members persist longer on average when the fluctuations of the members is small. In contrast, we find that the condition for stability for large communities is continuous changes in their membership, allowing for the possibility that after some time practically all members are exchanged.

Original languageEnglish
Title of host publicationNoise and Stochastics in Complex Systems and Finance
DOIs
StatePublished - 2007
Externally publishedYes
EventNoise and Stochastics in Complex Systems and Finance - Florence, Italy
Duration: 21 May 200724 May 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6601
ISSN (Print)0277-786X

Conference

ConferenceNoise and Stochastics in Complex Systems and Finance
Country/TerritoryItaly
CityFlorence
Period21/05/0724/05/07

Keywords

  • Communities
  • Community dynamics
  • Social networks
  • Time evolution

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