The identification of cohesive communities is a key process in social network analysis. However, the algorithms that are effective for finding communities do not scale well to very large problems, as their time complexity is worse than linear in the number of edges in the graph. This is an important issue for those interested in applying social network analysis techniques to very large networks, such as networks of mobile phone subscribers. In this respect the contributions of this report are two-fold. First we demonstrate these scaling issues using a prominent community-finding algorithm as a case study. We then show that a twostage process, whereby the network is first decomposed into manageable subnetworks using a multilevel graph partit...
The main subject of this thesis is to study the structure of communities in social networks and to d...
Online social networks showed an enormous growth in the last decade. With the rise of online social ...
Abstract — Finding decompositions of a graph into a family of clusters is crucial to understanding i...
The identification of cohesive communities is a key process in social network analysis. However, the...
Abstract. The identification of cohesive communities is a key process in social network analysis. Ho...
Communities have been a hot topic in complex network research the last years. Several algorithms for...
International audienceWe propose a simple method to extract the community structure of large network...
In this thesis, we first explore two different approaches to efficient community detection that addr...
Social networks usually display a hierarchy of communities and it is the task of community detection...
In a social network, small or large communities within the network play a major role in deciding the...
The increasing size and complexity of online social networks have brought distinct challenges to the...
With the help of information technologies, we have access to very large networks, even with billions...
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
Social network analysis is a cross-disciplinary study of interest to mathematicians, physicists, com...
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
The main subject of this thesis is to study the structure of communities in social networks and to d...
Online social networks showed an enormous growth in the last decade. With the rise of online social ...
Abstract — Finding decompositions of a graph into a family of clusters is crucial to understanding i...
The identification of cohesive communities is a key process in social network analysis. However, the...
Abstract. The identification of cohesive communities is a key process in social network analysis. Ho...
Communities have been a hot topic in complex network research the last years. Several algorithms for...
International audienceWe propose a simple method to extract the community structure of large network...
In this thesis, we first explore two different approaches to efficient community detection that addr...
Social networks usually display a hierarchy of communities and it is the task of community detection...
In a social network, small or large communities within the network play a major role in deciding the...
The increasing size and complexity of online social networks have brought distinct challenges to the...
With the help of information technologies, we have access to very large networks, even with billions...
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
Social network analysis is a cross-disciplinary study of interest to mathematicians, physicists, com...
We develop an algorithm to detect community structure in complex networks. The algorithm is based on...
The main subject of this thesis is to study the structure of communities in social networks and to d...
Online social networks showed an enormous growth in the last decade. With the rise of online social ...
Abstract — Finding decompositions of a graph into a family of clusters is crucial to understanding i...