Name
Abstract | ||
|---|---|---|
There has been growing evidence recently for the view that social networks can be divided into a well connected core, and a sparse periphery. This paper describes how such a global description can be obtained from local "dominance" relationships between vertices, to naturally yield a distributed algorithm for such a decomposition. It is shown that the resulting core describes the global structure of the network, while also preserving shortest paths, and displaying "expander-like" properties. Moreover, the periphery obtained from this decomposition consists of a large number of connected components, which can be used to identify communities in the network. These are used for a 'divide-and-conquer' strategy for community detection, where the peripheral components are obtained as a pre-processing step to identify the small sets most likely to contain communities. The method is illustrated using a real world network (DBLP co-authorship network), with ground-truth communities. |
Year | Venue | Keywords |
|---|---|---|
2015 | European Signal Processing Conference | Social networks,core-periphery structure,community detection,homology,local-to-global |
Field | DocType | ISSN |
Dynamic network analysis,Global structure,Social network,Vertex (geometry),Computer science,Network topology,Signal processing algorithms,Distributed computing | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jennifer Gamble | 1 | 4 | 1.15 |
| Harish Chintakunta | 2 | 36 | 6.05 |
| Hamid Krim | 3 | 520 | 59.69 |