Word Sense Induction (WSI) is an unsupervised approach for learning the multiple senses of a word. Graph-based approaches to WSI frequently represent word co-occurrence as a graph and use the statistical properties of the graph to identify the senses. We reinterpret graph-based WSI as community detection, a well studied problem in network science. The relations in the co-occurrence graph give rise to word communities, which distinguish senses. Our results show competitive performance on the SemEval-2010 WSI Task.