Networks are data structures more and more frequently used for modeling interactions in social and biological phenomena, as well as between various types of devices, tools and machines. They can be either static or dynamic, dependently on whether the modeled interactions are fixed or changeable over time. Static networks have been extensively investigated in data mining, while fewer studies hav...

We study by computer simulation a group of individuals playing the prisoner’s dilemma game with minimal information of their environment. The network of relationships between players, and their strategy can change over time following simple rules based on players’ degree of satisfaction and despair. We investigated both synchronous and asynchronous network dynamics, observing that cooperation c...

From Facebook groups and online gaming clans, to social movements and terrorist cells, groups of individuals aligned by interest, values or background are of increasing interest to social network researchers (Snow et al., 1980; Zheleva et al., 2009). In particular, understanding the structural and dynamic factors that influence the evolution of these groups remains an open challenge (Palla et a...

Currently, data management technologies are in the process of finding their way into evolving networks, i.e. P2P, ad hoc and wireless sensor networks. We examine the properties, differences and commonalities of the different types of evolving networks, in order to enable the development of adequate technologies 2 suiting their characteristics. We start with presenting definitions for the differ...

Recent studies of properties of various biological networks revealed that many of them display scale free characteristics. Since the theory of scale free networks is applicable to evolving networks, one can hope that it provides not only a model of a biological network in its current state but also some insight into the evolution of the network. Here, we re-investigate the probability distribut...

We consider “brane-universes”, where matter is confined to four-dimensional hypersurfaces (three-branes) whereas one extra compact dimension is felt by gravity only. We show that the cosmology of such branes is definitely different from standard cosmology and identify the reasons behind this difference. We give a new class of exact solutions with a constant five-dimensional radius and cosmologi...

This paper outlines a framework for the study of innovation that treats discoveries as additions to evolving networks. As inventions enter they expand or limit the reach of the ideas they build on by influencing how successive discoveries use those ideas. The approach is grounded in novel measures of the extent to which an innovation amplifies or disrupts the status quo. Those measures index th...

Roughly speaking, clustering evolving networks aims at detecting structurally dense subgroups in networks that evolve over time. This implies that the subgroups we seek for also evolve, which results in many additional tasks compared to clustering static networks. We discuss these additional tasks and difficulties resulting thereof and present an overview on current approaches to solve these pr...

In the past few years, the storage and analysis of large-scale and fast evolving networks present a great challenge. Therefore, a number of different techniques have been proposed for sampling large networks. In general, network exploration techniques approximate the original networks more accurately than random node and link selection. Yet, link selection with additional subgraph induction ste...

Community detection in social networks is a method that helps us to discover groups of users that are tightly connected. So far, most research has focused on detecting communities in static networks. However, networks evolve over time, and so do the communities within these networks. Understanding the evolution of communities is important to gain insight into macroscopic trends that drive chang...