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Characterizing ego-networks using motifs

Published online by Cambridge University Press:  19 September 2013

PÁDRAIG CUNNINGHAM
Affiliation:
School of Computer Science and Informatics, University College Dublin, Ireland (email: padraig.cunningham@ucd.ie)
MARTIN HARRIGAN
Affiliation:
School of Computer Science and Informatics, University College Dublin, Ireland (email: padraig.cunningham@ucd.ie)
GUANGYU WU
Affiliation:
School of Computer Science and Informatics, University College Dublin, Ireland (email: padraig.cunningham@ucd.ie)
DEREK O'CALLAGHAN
Affiliation:
School of Computer Science and Informatics, University College Dublin, Ireland (email: padraig.cunningham@ucd.ie)

Abstract

We assess the potential of network motif profiles to characterize ego-networks in much the same way that a bag-of-words strategy allows text documents to be compared in a vector space framework. This is potentially valuable as a generic strategy for comparing nodes in a network in terms of the network structure in which they are embedded. In this paper, we consider the computational challenges and model selection decisions involved in network motif profiling. We also present three case studies concerning the analysis of Wikipedia edit networks, YouTube spam campaigns, and peer-to-peer lending in the Prosper marketplace.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2013 

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