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Quantifying Social Group Evolution
Gergely Palla, Albert-Laszlo Barabasi, and Tamas VicsekNature Vol 446 April 2007
Presented by: Liang Ding Finance Department, KSU
Introduction• Complex community structure• Social and communication network
is subject to constant evolution• The knowledge of the mechanisms
governing the underlying community dynamics is limited
Intro cond• Aim: to uncover basic relationships
characterizing community evolution
• An algorithm based on clique percolation
data• 1. the monthly list of articles in the
Cornell University Library e-print condensed matter achieve spanning 142 months, with over 30,000 authors;
• 2. the record of phone calls of a mobile phone company spanning 52 weeks, 4 million users.
To check overlap•
• the average weight of the links inside communities
• the average weight of the inter- community links;
• For co-author is 2.9; for phone-call is 5.9• Indicating that the intensity of collaboration /com
munication within a group is significantly higher than with contacts belonging to a different group
cwicc ww /
icw
The time evolution of four communities from the co-authorship network show:
• A typical small and stationary community undergoes minor changes, but lives for a long time;
• A large non-stationary community whose members change dynamically, resulting in significant fluctuations in both size and composition, has a quite extended lifetime
Could the inspection of a community itself predict its
future?• wout: the total weight of this member’s
connections to outside of the community;
• win: the total weight of this member’s connections to members belonging to the same community;
• Calculate the probability that the member will abandon the community as a function of the wout/(win+wout) ratio