Abstract
We propose weighted line graphs for overlapping community discovery where a node in a network can be assigned to more than one community. For undirected connected networks without self-loops, we propose weighted line graphs by: (1) defining weights of a line graph based on the weights in the original network, and (2) removing self-loops in weighted line graphs, while sustaining their properties. By applying some off-the-shelf node partitioning method to the transformed graph, community labels of adjacent links are assigned to each node in the original network. Experiments are conducted over both synthetic and real-world networks, and the results indicate that the proposed approach can improve the quality of discovered overlapping communities.
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