Taxonomy of Cohesion Coefficients for Weighted and Directed Multilayer Networks
Paolo Bartesaghi, Gian Paolo Clemente, Rosanna Grassi

TL;DR
This paper introduces a systematic taxonomy of cohesion coefficients for weighted directed multilayer networks, extending classical measures with a new clumping coefficient and demonstrating their effectiveness through simulations.
Contribution
It develops a unified tensor-based framework for various cohesion coefficients, including a novel clumping coefficient, tailored for multilayer networks.
Findings
The new coefficients effectively capture network structure at multiple scales.
Tensor formalism unifies existing and new cohesion measures.
Applications show improved structural characterization of networks.
Abstract
Clustering and closure coefficients are among the most widely applied indicators in the description of the topological structure of a network. Many distinct definitions have been proposed over time, particularly in the case of weighted networks, where the choice of the weight attributed to the triangles is a crucial aspect. In the present work, in the framework of weighted directed multilayer networks, we extend the classical clustering and closure coefficients through the introduction of the clumping coefficient, which generalizes them to incomplete triangles of any type. We then organize the class of these coefficients in a systematic taxonomy in the more general context of weighted directed multilayer networks. Such cohesion coefficients have also been adapted to the different scales that characterize a multilayer network, in order to grasp their structure from different…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques · Network Traffic and Congestion Control
