Networks (or graphs) appear as dominant structures in diverse domains, including
sociology, biology, neuroscience and computer science. In most of the aforementioned …

Link prediction in complex networks has attracted increasing attention from both physical
and computer science communities. The algorithms can be used to extract missing …

Stochastic blockmodels have been proposed as a tool for detecting community structure in
networks as well as for generating synthetic networks for use as benchmarks. Most …

The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

Discovering and characterizing the large-scale topological features in empirical networks
are crucial steps in understanding how complex systems function. However, most existing …

The authors consider processes on social networks that can potentially involve three factors:
homophily, or the formation of social ties due to matching individual traits; social contagion …

“But although, as a matter of history, statistical mechanics owes its origin to investigations in
thermodynamics, it seems eminently worthy of an independent development, both on …

The current economic crisis illustrates a critical need for new and fundamental
understanding of the structure and dynamics of economic networks. Economic systems are …

Detecting communities in complex networks accurately is a prime challenge, preceding
further analyses of network characteristics and dynamics. Until now, community detection …

We investigate the detectability of modules in large networks when the number of modules is
not known in advance. We employ the minimum description length principle which seeks to …