A key issue in social network analysis is related to the comparison between K observed networks. To this end, a special graph embedding procedure within the so-called dissimilarity representation framework is proposed. The procedure is mainly based on the use of an appropriate metric among the observed networks, that is the graph edit distance. Particular attention is devoted also to the dimensionality reduction of the embedding. The purpose is to provide a measure of the distances among the K observed networks, embedding them as points in a multivariate space.We will show applications in both exploratory social network analysis and network statistical modeling.
Graph embedding via dissimilarity mapping for network comparison
DE STEFANO, DOMENICO
2012-01-01
Abstract
A key issue in social network analysis is related to the comparison between K observed networks. To this end, a special graph embedding procedure within the so-called dissimilarity representation framework is proposed. The procedure is mainly based on the use of an appropriate metric among the observed networks, that is the graph edit distance. Particular attention is devoted also to the dimensionality reduction of the embedding. The purpose is to provide a measure of the distances among the K observed networks, embedding them as points in a multivariate space.We will show applications in both exploratory social network analysis and network statistical modeling.Pubblicazioni consigliate
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