On Filtering the Noise in Consensual Communities

Community detection is a tool to understand how networks are organised. Ranging from social, technological, information or biological networks, many real-world networks exhibit a community structure. Consensual community detection fixes some of the issues of classical community detection like non-determinism. This is often done through what is called a consensus matrix. We show that this consensus matrix is not filled with relevant information only, it is noisy. We then show how to filter out some of the noise and how it could benefit existing algorithms.