In this paper, we present an alternate algorithm for detecting overlapping community structures in the complex network. Two concepts named the maximal sub-graph and the clustering coefficient between two neighboring communities are introduced. First, all the maximal sub-graphs are extracted from...

A complex network is a powerful tool to research complex systems, traffic flow being one of the most complex systems. In this paper, we use complex network theory to study traffic time series, which provide a new insight into traffic flow analysis. Firstly, the phase space, which describes the...

Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model...

In this paper, we develop a general analytical method to compute clustering coefficients of growing networks. This method can be applied to any network as long as we can construct and solve the dynamic equation for the degree of any node. We also verify the accuracy of the method through simulation.

By incorporating local traffic information into the basic shortest path routing policy, we propose a congestion awareness routing strategy with a tunable parameter. We investigate the effectiveness of the proposed routing strategy for scale-free networks with different clustering coefficients...

We propose several characterizations of weighted complex networks by incorporating the concept of metaweight into the clustering coefficient, degree correlation, and module decomposition. These incorporations make it possible to describe weighted networks depending on how strongly we emphasize...

Dynamic processes in complex networks have received much attention. This attention reflects the fact that dynamic processes are the main source of changes in the structural properties of complex networks (e.g., clustering coefficient and average shortest-path length). In this paper, we develop...

When we study the architecture of networks of spatially extended systems the nodes in the network are subject to local correlation structures. In this case, we show that for scale-free networks the traditional way to estimate the clustering coefficient may not be meaningful. Here we explain why...

In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this...

In this study, we examine a seismic network by considering the cell resolution and the temporal causality. Seismic activity data from the Korean peninsula are mapped onto a growing network with links between consecutive events. After we especially show a seismic network with spatial...