Diffusion centrality in social networks

Chanhyun Kang*, Cristian Molinaro, Sarit Kraus, Yuval Shavitt, V. S. Subrahmanian

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Though centrality of vertices in social networks has been extensively studied, all past efforts assume that centrality of a vertex solely depends on the structural properties of graphs. However, with the emergence of online "semantic" social networks where vertices have properties (e.g. gender, age, and other demographic data) and edges are labeled with relationships (e.g. friend, follows) and weights (measuring the strength of a relationship), it is essential that we take semantics into account when measuring centrality. Moreover, the centrality of a vertex should be tied to a diffusive property in the network - a Twitter vertex may have high centrality w.r.t. jazz, but low centrality w.r.t. Republican politics. In this paper, we propose a new notion of diffusion centrality (DC) in which semantic aspects of the graph, as well as a diffusion model of how a diffusive property p is spreading, are used to characterize the centrality of vertices. We present a hypergraph based algorithm to compute DC and report on a prototype implementation and experiments showing how we can compute DCs (using real YouTube data) on social networks in a reasonable amount of time. We compare DC with classical centrality measures like degree, closeness, betweenness, eigenvector and stress centrality and show that in all cases, DC produces higher quality results. DC is also often faster to compute than both betweenness, closeness and stress centrality, but slower than degree and eigenvector centrality.

Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Pages558-564
Number of pages7
DOIs
StatePublished - 2012
Event2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey
Duration: 26 Aug 201229 Aug 2012

Publication series

NameProceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012

Conference

Conference2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Country/TerritoryTurkey
CityIstanbul
Period26/08/1229/08/12

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