Identifying modular network structure is generally a problem of finding the correct community mem... more Identifying modular network structure is generally a problem of finding the correct community membership of each node in a network. An alternative approach, clustering links, naturally accounts for real world characteristics such as strong community overlap, multi-partite structure, and hierarchical organization. By introducing a pair-wise link similarity, we use a hierarchical clustering method to identify relevant communities in real-world examples
We propose a new viewpoint for the problem of community detection in complex networks. Rather tha... more We propose a new viewpoint for the problem of community detection in complex networks. Rather than defining a community as a set of densely interconnected nodes, we define a community as a set of (related) links. We show how this alternative viewpoint incorporates significant aspects including overlapping communities. A quantitative framework for evaluating the link partitions is also introduced.
Many systems, from power grids and the internet, to the brain and society, can be modeled using n... more Many systems, from power grids and the internet, to the brain and society, can be modeled using networks of coupled overlapping modules. The elements of these networks perform individual and collective tasks such as generating and consuming electrical load or transmitting data. We study the robustness of these systems using percolation theory: a random fraction of the elements fail which
Identifying modular network structure is generally a problem of finding the correct community mem... more Identifying modular network structure is generally a problem of finding the correct community membership of each node in a network. An alternative approach, clustering links, naturally accounts for real world characteristics such as strong community overlap, multi-partite structure, and hierarchical organization. By introducing a pair-wise link similarity, we use a hierarchical clustering method to identify relevant communities in real-world examples
We propose a new viewpoint for the problem of community detection in complex networks. Rather tha... more We propose a new viewpoint for the problem of community detection in complex networks. Rather than defining a community as a set of densely interconnected nodes, we define a community as a set of (related) links. We show how this alternative viewpoint incorporates significant aspects including overlapping communities. A quantitative framework for evaluating the link partitions is also introduced.
Many systems, from power grids and the internet, to the brain and society, can be modeled using n... more Many systems, from power grids and the internet, to the brain and society, can be modeled using networks of coupled overlapping modules. The elements of these networks perform individual and collective tasks such as generating and consuming electrical load or transmitting data. We study the robustness of these systems using percolation theory: a random fraction of the elements fail which
Uploads
Papers by S. Lehmann