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 investigate wealth distribution on scale-free networks with different consumption strategies. We indicate that nonlinear consumption function can lead to exponential wealth distribution with a power law tail in accordance with empirical data. In addition, we suggest that anti-degree...

Nowadays the propagation of human activity, especially health behavior, has become a significant issue in the study of online social network. Considering the effect of human behavior on information diffusion in social networks (Centola, 2010), we propose a simple...

Group interactions on structured populations can be represented by the public goods game on networks. During the evolutionary games, selective investment mechanism fosters social cooperative behavior. First we focus on star-like graphs to provide some light on why selective investment mechanism...

Rumor diffusion on complex networks has been widely investigated assuming that an individual learns the rumor merely from its neighbors, which, however, is not always the case. Recent studies of layered models have shown that individuals belonging to many different networks can affect the...

In this paper, we propose a well targeted algorithm (GAS algorithm) for detecting communities in high clustered networks by presenting group action technology on community division. During the processing of this algorithm, the underlying community structure of a clustered network emerges...

In this paper, we introduce a non-interacting boson model to investigate the topological structure of complex networks. By exactly solving this model, we show that it provides a powerful analytical tool in uncovering the important properties of realistic networks. We find that the ground-state...

Most real-world networks from various fields share a universal topological property as community structure. In this paper, we propose a node-similarity based mechanism to explore the formation of modular networks by applying the concept of hidden metric spaces of complex networks. It is...