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ASUNAM
2009
IEEE

Social Network Discovery Based on Sensitivity Analysis

11 years 8 months ago
Social Network Discovery Based on Sensitivity Analysis
—This paper presents a novel methodology for social network discovery based on the sensitivity coefficients of importance metrics, namely the Markov centrality of a node, a metric based on random walks. Analogous to node importance, which ranks the important nodes in a social network, the sensitivity analysis of this metric provides a ranking of the relationships between nodes. The sensitivity parameter of the importance of a node with respect to another measures the direct or indirect impact of a node. We show that these relationships help discover hidden links between nodes and highlight meaningful links between seemingly disparate sub-networks in a social structure. We introduce the notion of implicit links, which represent an indirect relationship between nodes not connected by edges, which represent hidden connections in complex networks. We demonstrate our methodology on two social network data sets and use sensitivity-guided visualizations to highlight our findings. Our resu...
Tarik Crnovrsanin, Carlos D. Correa, Kwan-Liu Ma
Added 18 May 2010
Updated 18 May 2010
Type Conference
Year 2009
Where ASUNAM
Authors Tarik Crnovrsanin, Carlos D. Correa, Kwan-Liu Ma
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