Why social networks are different from other types of networks

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We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have nontrivial clustering or network transitivity and second, they show positive correlations, also called assortative mixing, between the degrees of adjacent vertices. Social networks are often divided into groups or communities, and it has recently been suggested that this division could account for the observed clustering. We demonstrate that group structure in networks can also account for degree correlations. We show using a simple model that we should expect assortative mixing in such networks whenever there is variation in the sizes of the groups and that the predicted level of assortative mixing compares well with that observed in real-world networks.
Publisher
AMER PHYSICAL SOC
Issue Date
2003-09
Language
English
Article Type
Article
Citation

PHYSICAL REVIEW E, v.68, no.3

ISSN
1539-3755
DOI
10.1103/PhysRevE.68.036122
URI
http://hdl.handle.net/10203/85989
Appears in Collection
GCT-Journal Papers(저널논문)
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