Community structure extraction in directed network using triads

Community detection in directed networks appears as one of the most relevant topics in the field of network analysis. One of the common themes in its formalizations is information flow clustering in a network. Such clusters can be extracted by using triads, expected to play an important role in the detection of that type of communities since communities could be centered round core nodes calledkernels. Triads in directed graphs are directed sub-graphs of three nodes involving at least two links between them. To identify communities in directed networks, this paper proposes an in-seed-centric scheme based on directed triads. We also propose a new metric of the communities' quality based on the triad density of communities. To validate our approach, an experiment was conducted on some networks showing it has better performance on triad-based density over some state-of-the-art methods.