In this paper, we present a local method for detecting communities in networks. We define an outside rate coefficient ψout in our method. ψout has a very simple form and is easy to calculate. The local community enclosing a starting node can be detected by agglomerating the node with the...

In this paper, we analyze an evolving model with local information which can generate a class of networks by choosing different values of the parameter p. The model introduced exhibits the transition from unweighted networks to weighted networks because the distribution of the edge weight can be...

Phenomenon of asymmetry between odd and even node weight distribution in some complex networks, such as public transportation networks and Internet, is presented. Reasons related to this phenomenon are summarized, i.e., (1) edges are solid connections between nodes which are embedded in real...

The study of opinion dynamics, such as spreading and controlling of rumors, has become an important issue on social networks. Numerous models have been devised to describe this process, including epidemic models and spin models, which mainly focus on how opinions spread and interact with each...

We study the growth of networks from a set of isolated ground nodes by the addition of one new node per time step and also of a fixed number of directed edges leading from the new node to randomly selected nodes already in the network. A fixed-width time window is used so that, in general, only...

In this paper we define a new class of weighted complex networks sharing several properties with fractal sets, and whose topology can be completely analytically characterized in terms of the involved parameters and of the fractal dimension. General networks with fractal or hierarchical...

In this paper, a new method is presented to analyze the linear stability of the synchronized state in arbitrarily coupled complex dynamical systems with time delays. The coupling configurations are not restricted to the symmetric and irreducible connections or the non-negative off-diagonal...

We extend the study of a model of competitive cluster growth in an active medium from a regular topology to a complex network topology; this is done by adding nonlocal connections with probability p to sites on a regular lattice, thus enabling one to interpolate between regularity and full...

Plenty of algorithms for link prediction have been proposed to extract missing information, identify spurious interactions, reconstruct networks, and so on. Stochastic block models are one of the most accurate methods among all of them. However, this algorithm is designed only for simple graphs...

In this work, we propose and study a model for the diffusion of congestion in complex networks. According to the proposed model, the level of congestion on each node will be self-organized into the same value. The diffusion of congestion throughout various networks with different topologies is...