Study of higher-order interactions in unweighted, undirected networks using persistent homology
Udit Raj, Slobodan Maleti\'c, Sudeepto Bhattacharya

TL;DR
This paper explores higher-order interactions in unweighted, undirected networks using persistent homology, introducing new measures and filtration schemes to analyze complex network topology beyond pairwise connections.
Contribution
It develops a novel framework for studying higher-order network structures via persistent homology, including new global and local measures and multiple filtration schemes.
Findings
Introduced weighted simplicial adjacency matrix based on clique complexes.
Calculated Betti numbers up to dimension two for real-world network analysis.
Compared topology of higher-order structures using different filtration schemes.
Abstract
Persistent homology has been studied to better understand the structural properties and topology features of weighted networks. It can reveal hidden layers of information about the higher-order structures formed by non-pairwise interactions in a network. Studying of higher-order interactions (HoIs) of a system provides a more comprehensive understanding of the complex system; moreover, it is a more precise depiction of the system as many complex systems, such as ecological systems and biological systems, etc., demonstrate HoIs. In this study, the weighted simplicial adjacency matrix has been constructed using the concept of adjacency strength of simplices in a clique complex obtained from an unweighted, undirected network. This weighted simplicial adjacency matrix is thus used to calculate the global measure, which is called generalised weighted betweenness centrality, which further…
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Taxonomy
TopicsTopological and Geometric Data Analysis
