Please use this identifier to cite or link to this item: http://ktisis.cut.ac.cy/handle/10488/5831
Title: Popularity versus similarity in growing networks
Authors: Papadopoulos, Fragkiskos 
Keywords: Applied physics
Engineering
Physics
Issue Date: 2012
Publisher: Macmillan Publishers
Source: Nature, 2012, Volume 489, Number 7417, Pages 537–540
Abstract: The principle that popularity is attractive underlies preferential attachment, which is a common explanation for the emergence of scaling in growing networks. If new connections are made preferentially to more popular nodes, then the resulting distribution of the number of connections possessed by nodes follows power laws as observed in many real networks. Preferential attachment has been directly validated for some real networks (including the Internet), and can be a consequence of different underlying processes based on node fitness, ranking, optimization, random walks or duplication. Here we show that popularity is just one dimension of attractiveness; another dimension is similarity. We develop a framework in which new connections optimize certain trade-offs between popularity and similarity, instead of simply preferring popular nodes. The framework has a geometric interpretation in which popularity preference emerges from local optimization. As opposed to preferential attachment, our optimization framework accurately describes the large-scale evolution of technological (the Internet), social (trust relationships between people) and biological (Escherichia coli metabolic) networks, predicting the probability of new links with high precision. The framework that we have developed can thus be used for predicting new links in evolving networks, and provides a different perspective on preferential attachment as an emergent phenomenon.
URI: http://ktisis.cut.ac.cy/handle/10488/5831
ISSN: 0028-0836
1476-4687
DOI: 10.1038/nature11459
Appears in Collections:Άρθρα/Articles

Show full item record

SCOPUSTM   
Citations 1

135
checked on Dec 2, 2016

WEB OF SCIENCETM
Citations 5

112
checked on Nov 25, 2016

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.