Authors: Dietrich Steinmetz, Hui Ma, Sven Hartmann, Vladivy Poaka
Tags: 2016, conceptual modeling
Label propagation is a very popular, simple and fast algorithm for detecting communities in a graph such as a social network. However, it known to be non-deterministic, unstable and not very accurate. These shortcoming have attracted much attention by the research community, and many improvements have been suggested. In this paper we propose an new approach for computing preference to stabilize label propagation. The idea is to exploit the structure of the graph at study and use the link density to determine the preference of nodes. Our approach do not require any input parameter aside from the input graph itself. The complexity of propagation-based is slightly increased, but the stabilization and determinism are almost reached. Furthermore, we also propose a fuzzy version of our approach that allows one to detect overlapping communities as common in social networks. We have tested our algorithms with various real-world social networks.Read the full paper here: https://link-springer-com.proxy2.hec.ca/chapter/10.1007/978-3-319-47717-6_7
