Title
Multilayer weighted social network model.
Abstract
Recent empirical studies using large-scale data sets have validated the Granovetter hypothesis on the structure of the society in that there are strongly wired communities connected by weak ties. However, as interaction between individuals takes place in diverse contexts, these communities turn out to be overlapping. This implies that the society has a multilayered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, a sufficient amount of interlayer correlation is needed to maintain the relationship between topology and link weights, while these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multilayer WSN model, where the indirect interlayer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at the same time, the Granovetterian structure is preserved.
Year
DOI
Venue
2014
10.1103/PhysRevE.90.052810
PHYSICAL REVIEW E
DocType
Volume
Issue
Journal
90
5
ISSN
Citations 
PageRank 
1539-3755
7
0.63
References 
Authors
0
5
Name
Order
Citations
PageRank
Yohsuke Murase170.63
János Török270.97
Hang-Hyun Jo370.63
Kimmo Kaski4101.01
János Kertész570.63