2010
Conference article  Open Access

As time goes by: discovering eras in evolving social networks

Berlingerio M., Coscia M., Giannotti F., Monreale A., Pedreschi D.

Social Network Analysis  Database Management  68P20 

Within the large body of research in complex network analysis, an important topic is the temporal evolution of networks. Existing approaches aim at analyzing the evolution on the global and the local scale, extracting properties of either the entire network or local patterns. In this paper, we focus instead on detecting clusters of temporal snapshots of a network, to be interpreted as eras of evolution. To this aim, we introduce a novel hierarchical clustering methodology, based on a dissimilarity measure (derived from the Jaccard coefficient) between two temporal snapshots of the network. We devise a framework to discover and browse the eras, either in top-down or a bottom-up fashion, supporting the exploration of the evolution at any level of temporal resolution. We show how our approach applies to real networks, by detecting eras in an evolving co-authorship graph extracted from a bibliographic dataset; we illustrate how the discovered temporal clustering highlights the crucial moments when the network had profound changes in its structure. Our approach is finally boosted by introducing a meaningful labeling of the obtained clusters, such as the characterizing topics of each discovered era, thus adding a semantic dimension to our analysis.

Source: PAKSS 2010 - Advances in Knowledge Discovery and Data Mining. 14th Pacific-Asia Conference, pp. 81–90, Hyderabad, India, 21-24 June


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:44349,
	title = {As time goes by: discovering eras in evolving social networks},
	author = {Berlingerio M. and Coscia M. and Giannotti F. and Monreale A. and Pedreschi D.},
	doi = {10.1007/978-3-642-13657-3_11},
	booktitle = {PAKSS 2010 - Advances in Knowledge Discovery and Data Mining. 14th Pacific-Asia Conference, pp. 81–90, Hyderabad, India, 21-24 June},
	year = {2010}
}