DocumentCode
183992
Title
Characterizing the relationship between degree distributions and community structures
Author
Moriano, Pablo ; Finke, Jorge
Author_Institution
Sch. of Inf. & Comput., Indiana Univ., Bloomington, IN, USA
fYear
2014
fDate
4-6 June 2014
Firstpage
2383
Lastpage
2388
Abstract
Extended power laws and inhomogeneous connections are structural patterns often found in empirical networks. Mechanisms based on the formation of triads are able to explain the power law behavior of the degree distribution of such networks. The proposed model introduces a two-step mechanism of attachment and triad formation that illustrates how preferential linkage plays an important role in shaping the inhomogeneity of connections and the division of the network into groups of nodes (i.e., the growth of community structures). In particular, we identify conditions under which the scaling exponent of the power law correlates to a widely-used modularity measure of non-overlapping communities. Our analytical results characterize the asymptotic behavior of both the scaling exponent and the modularity, as a function of the strength with which nodes with similar characteristics tend to link to each other.
Keywords
asymptotic stability; interconnected systems; asymptotic behavior; community structures; degree distributions; empirical networks; extended power laws; inhomogeneous connections; modularity measure; nonoverlapping communities; power law behavior; preferential linkage; structural patterns; Communities; Correlation; Educational institutions; Indexes; Mathematical model; Nonhomogeneous media; Q measurement; Control of networks; Modeling and simulation; Stochastic systems;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6858882
Filename
6858882
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