The investigation of community structure in networks is a task of great importance in many disciplines, namely physics, sociology, biology and computer science where systems are often represented as graphs. One of the challenges is to find local communities from a local viewpoint in a graph without global information in order to reproduce the subjective hierarchical vision for each vertex. In t...

To test for direct and indirect effects of a top predator on three lower trophic levels, we conducted two multiyear predator addition experiments in a tropical wet forest. Periodic additions of a top predator (predatory clerid beetle) to a wet forest understory shrub caused a reduction in the predatory beetle's prey (a predatory ant), increased herbivory, and reduced leaf area of the plant. The...

Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edg...

In this paper, we establish the definition of community fundamentally different from what was commonly accepted in previous studies, where communities were typically assumed to be densely connected internally but sparsely connected to the rest of the network. A community should be considered as a densely connected subset in which the probability of an edge between two randomly-picked vertices i...

Community detection is one of the pivotal tools for discovering the structure of complex networks. Majority of community detection methods rely on optimization of certain quality functions characterizing the proposed community structure. Perhaps, the most commonly used of those quality functions is modularity. Many heuristics are claimed to be efficient in modularity maximization, which is usua...

Recently,various heterogeneous complex networks featured as “small-world” and “scale-free” have become a common research area of different disciplines. Especially, network topology mining and community detection have become focal topics. Through the investigations of typical features in complex networks, we propose a network nodes evaluation model based on a multivariate hierarchy method. With ...

Community structure identification has been one of the most popular research areas in recent years due to its applicability to the wide scale of disciplines. To detect communities in varied topics, there have been many algorithms proposed so far. However, most of them still have some drawbacks to be addressed. In this paper, we present an agent-based based community detection algorithm. The alg...

Blocking the propagation of contagions in populations has many applications, such as stopping the dissemination of leaked information and impeding the spread of an ideology or opinion. Several methods exist for blocking contagions by removing key or critical nodes from a network representation of a population. Some methods, based on network topology alone, run very fast, but their performance c...