Detecting multiple stochastic network motifs in network data
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
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Motifs are small subgraphs showing statistically significant occurrence in given network. Motif analysis helps to insight into the local topology and functions of complex networks. The social position measure is interpreted as the importance of the node (user) within the network. We propose to fuse motif analysis with the social position assessment by colouring the nodes according to the measured position. As the distribution of discovered coloured motifs is utilized to mine the interconnection patterns between nodes, the results allow us to evaluate the influence of social position on the local topology of network connections. The experiment was carried out on the large social network derived from email communication.