Quantifying social group evolution

Description

The rich set of interactions between individuals in society1–7
results in complex community structure, capturing highly connected
circles of friends, families or professional cliques in a social
network3,7–10. Thanks to frequent changes in the activity and communication
patterns of individuals, the associated patterns of individuals, the associated social and communication
network is subject to constant evolution7,11–16. Our
knowledge of the mechanisms governing the underlying community
dynamics is limited, but is essential for a deeper understanding
of the development and self-optimization of society as a whole17–22.
We have developed an algorithm based on clique percolation23,24
that allows us to investigate the time dependence of overlapping
communities on a large scale, and thus uncover basic relationships
characterizing community evolution. Our focus is on networks
capturing the collaboration between scientists and the calls between
mobile phone users. We find that large groups persist for
longer if they are capable of longer if they are capable of dynamically altering their membership,
suggesting that an ability to change the group composition
results in better adaptability. The behaviour of small groups displays
the opposite tendency—the condition for stability is that
their composition remains unchanged. their composition remains unchanged. We also show that knowledge
of the time commitment of members to a given community
can be used for estimating the community’s lifetime. These findings
offer insight into the fundamental differences between the
dynamics of small groups and large institutions.

Original URL

http://www.nd.edu/~alb/Publication06/142-SocialGroup_Nature-5Apr07-CN/SocialGroup_Nature-5Apr07.pdf

http://www.nd.edu/~alb/Publication06/142-SocialGroup_Nature-5Apr07-CN/SocialGroup_Nature-5Apr07.pdf