KEYWORDS: Social networks, Algorithm development, Mobile communications, Cell phones, Physics, Stochastic processes, Complex systems, Data archive systems, Data communications, Data processing
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.
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