Most of the massive ubiquitous networks in our day to day life are evolving in real time. Be it the network of persons, entities, genes, sensors or their combinations, they are inherently complex and evolving with nodes appearing, disappearing, associating and disassociating with each other as time flies. In fact, most real-life networks evolve in a wide variety of ways that lead to different kinds of evolution semantics. While a deep foundation has been developed in the past years on analytics on complex networks, relatively little progress has been made when considering evolving networks.

The scalability issues also keep growing alongside networks. In the light of above complexities, this special session welcomes novel research about mining and analytics in networks that evolve over time. We are interested since foundation methods that make feasible the analysis of large dynamic networks, like distributed processing, streaming, incremental algorithms, sampling etc., until pattern mining and predictive modeling tasks on evolving networks, such as community detection and event mining. We also encourage submissions exploring applications over evolving network data. The objective of this special session is to bring together researchers from different communities in this emerging topic.