Title
Preferential attachment in online networks: measurement and explanations
Abstract
We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of network considered. The classical preferential attachment model for networks by Barabási and Albert (1999) assumes a linear relationship between the number of neighbors of a node in a network and the probability of attachment. Although this assumption is widely made in Web Science and related fields, the underlying linearity is rarely measured. To fill this gap, this paper performs an empirical longitudinal (time-based) study on forty-seven diverse Web network datasets from seven network categories and including directed, undirected and bipartite networks. We show that contrary to the usual assumption, preferential attachment is nonlinear in the networks under consideration. Furthermore, we observe that the deviation from linearity is dependent on the type of network, giving sublinear attachment in certain types of networks, and superlinear attachment in others. Thus, we introduce the preferential attachment exponent β as a novel numerical network measure that can be used to discriminate different types of networks. We propose explanations for the behavior of that network measure, based on the mechanisms that underly the growth of the network in question.
Year
DOI
Venue
2013
10.1145/2464464.2464514
Proceedings of the 5th Annual ACM Web Science Conference
Keywords
DocType
Volume
nonlinear preferential attachment model,classical preferential attachment model,bipartite network,network category,preferential attachment phenomenon,network measure,preferential attachment exponent,online network,preferential attachment,novel numerical network measure,forty-seven diverse web network,network analysis
Conference
abs/1303.6271
Citations 
PageRank 
References 
17
1.07
31
Authors
3
Name
Order
Citations
PageRank
Jérôme Kunegis187451.20
Marcel Blattner2183.01
Christine Moser3262.67