TY - GEN

T1 - Fixed points of graph peeling

AU - Abello, James

AU - Queyroi, François

PY - 2013

Y1 - 2013

N2 - Degree peeling is used to study complex networks. It corresponds to a decomposition of the graph into vertex groups of increasing minimum degree. However, the peeling value of a vertex is non-local in this context since it relies on the connections the vertex has to groups above it. We explore a different way to decompose a network into edge layers such that the local peeling value of the vertices on each layer does not depend on their non-local connections with the other layers. This corresponds to the decomposition of a graph into subgraphs that are invariant with respect to degree peeling, i.e. they are fixed points. We introduce in this context a method to partition the edges of a graph into fixed points of degree peeling, called the iterative-edge-core decomposition. Information from this decomposition is used to formulate a notion of vertex diversity based on Shannon's entropy. We illustrate the usefulness of this decomposition in social network analysis. Our method can be used for community detection and graph visualization.

AB - Degree peeling is used to study complex networks. It corresponds to a decomposition of the graph into vertex groups of increasing minimum degree. However, the peeling value of a vertex is non-local in this context since it relies on the connections the vertex has to groups above it. We explore a different way to decompose a network into edge layers such that the local peeling value of the vertices on each layer does not depend on their non-local connections with the other layers. This corresponds to the decomposition of a graph into subgraphs that are invariant with respect to degree peeling, i.e. they are fixed points. We introduce in this context a method to partition the edges of a graph into fixed points of degree peeling, called the iterative-edge-core decomposition. Information from this decomposition is used to formulate a notion of vertex diversity based on Shannon's entropy. We illustrate the usefulness of this decomposition in social network analysis. Our method can be used for community detection and graph visualization.

UR - http://www.scopus.com/inward/record.url?scp=84893246967&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893246967&partnerID=8YFLogxK

U2 - 10.1145/2492517.2492543

DO - 10.1145/2492517.2492543

M3 - Conference contribution

AN - SCOPUS:84893246967

SN - 9781450322409

T3 - Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013

SP - 256

EP - 263

BT - Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013

PB - Association for Computing Machinery

T2 - 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013

Y2 - 25 August 2013 through 28 August 2013

ER -