Title
A stochastic evolutionary growth model for social networks
Abstract
We present a stochastic model for a social network, where new actors may join the network, existing actors may become inactive and, at a later stage, reactivate themselves. Our model captures the evolution of the network, assuming that actors attain new relations or become active according to the preferential attachment rule. We derive the mean-field equations for this stochastic model and show that, asymptotically, the distribution of actors obeys a power-law distribution. In particular, the model applies to social networks such as wireless local area networks, where users connect to access points, and peer-to-peer networks where users connect to each other. As a proof of concept, we demonstrate the validity of our model empirically by analysing a public log containing traces from a wireless network at Dartmouth College over a period of three years. Analysing the data processed according to our model, we demonstrate that the distribution of user accesses is asymptotically a power-law distribution.
Year
DOI
Venue
2007
10.1016/j.comnet.2007.06.013
Computer Networks
Keywords
DocType
Volume
Social network,Power-law distribution,Stochastic evolutionary growth model,Preferential attachment
Journal
51
Issue
ISSN
Citations 
16
Computer Networks
5
PageRank 
References 
Authors
0.46
14
4
Name
Order
Citations
PageRank
Trevor Fenner1487.17
Mark Levene21272252.84
George Loizou3759218.32
George Roussos4796.28