Network community-detection enhancement by proper weighting.

In this paper, we show how proper assignment of weights to the edges of a complex network can enhance the detection of communities and how it can circumvent the resolution limit and the extreme degeneracy problems associated with modularity. Our general weighting scheme takes advantage of graph theoretic measures and it introduces two heuristics for tuning its parameters. We use this weighting as a preprocessing step for the greedy modularity optimization algorithm of Newman to improve its performance.

Comment on "Rewiring networks for synchronization" [Chaos 18, 037105 (2008)].

This is a comment on a recent paper by A. Hagberg and D. A.

Efficient rewirings for enhancing synchronizability of dynamical networks.

In this paper, we present an algorithm for optimizing synchronizability of complex dynamical networks. Starting with an undirected and unweighted network, we end up with an undirected and unweighted network with the same number of nodes and edges having enhanced synchronizability. To this end, based on some network properties, rewirings, i.

Enhancing synchronizability of weighted dynamical networks using betweenness centrality.

By considering the eigenratio of the Laplacian of the connection graph as a synchronizability measure, we propose a procedure for weighting dynamical networks to enhance their synchronizability. The method is based on node and edge betweenness centrality measures and is tested on artificially constructed scale-free, Watts-Strogatz, and random networks as well as on some real-world graphs. It is also numerically shown that the same procedure could be used to enhance the phase synchronizability of networks of nonidentical oscillators.