The widespread adoption of digitization has opened the way to gathering large amounts of data that record detailed information for many systems of interest. Examples include telecommunication networks, online social-media platforms, and biological systems. Many of these systems are typically represented as networks, and graph-theoretic techniques are used to analyze the available data. Furthermore, as our data-gathering capacity has increased, it is now possible to collect data the record not only a static aggregate view of the underlying network, but a continuous stream of events that captures the full dynamic behavior of the network. Such events may take the form of structural changes, or they may encode different types of actions and interactions performed by the network entities. This view of time-evolving networks poses new challenges and opens new research directions. The objective is to develop the theoretical foundations and to design the algorithmic principles that will allow to efficiently manage and analyze such evolving networks.
Read more about it here. Submissions are due Oct 15, 2015.