Research output: Contribution to conference › Paper › peer-review
Beta Current Flow Centrality for Weighted Networks. / Avrachenkov, Konstantin E.; Mazalov, Vladimir V.; Tsynguev, Bulat T.
2015. 216-227 Paper presented at 4th International Conference Computational Social NetworksResearch output: Contribution to conference › Paper › peer-review
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TY - CONF
T1 - Beta Current Flow Centrality for Weighted Networks
AU - Avrachenkov, Konstantin E.
AU - Mazalov, Vladimir V.
AU - Tsynguev, Bulat T.
PY - 2015
Y1 - 2015
N2 - Betweenness centrality is one of the basic concepts in the analysis of social networks. Initial definition for the betweenness of a node in a graph is based on the fraction of the number of geodesics (shortest paths) between any two nodes that given node lies on, to the total number of the shortest paths connecting these nodes. This method has quadratic complexity and does not take into account indirect paths. We propose a new concept of betweenness centrality for weighted network, beta current flow centrality, based on Kirchhoff’s law for electric circuits. In comparison with the original current flow centrality and alpha current flow centrality, this new measure can be computed for larger networks. The results of numerical experiments for some examples of networks, in particular, for the popular social network VKontakte as well as the comparison with PageRank method are presented.
AB - Betweenness centrality is one of the basic concepts in the analysis of social networks. Initial definition for the betweenness of a node in a graph is based on the fraction of the number of geodesics (shortest paths) between any two nodes that given node lies on, to the total number of the shortest paths connecting these nodes. This method has quadratic complexity and does not take into account indirect paths. We propose a new concept of betweenness centrality for weighted network, beta current flow centrality, based on Kirchhoff’s law for electric circuits. In comparison with the original current flow centrality and alpha current flow centrality, this new measure can be computed for larger networks. The results of numerical experiments for some examples of networks, in particular, for the popular social network VKontakte as well as the comparison with PageRank method are presented.
U2 - 10.1007/978-3-319-21786-4_19
DO - 10.1007/978-3-319-21786-4_19
M3 - Paper
SP - 216
EP - 227
Y2 - 3 August 2015 through 5 August 2015
ER -
ID: 134825752