Saved in:
Bibliographic Details
Main Author: Riane, Nizar
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2305.02371
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916496866803712
author Riane, Nizar
author_facet Riane, Nizar
contents This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph's adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing for overlaps. To illustrate our method, we apply it to input-output analysis within the context of the Moroccan economy.
format Preprint
id arxiv_https___arxiv_org_abs_2305_02371
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Spectral influence in networks: An application to Input-Output analysis
Riane, Nizar
Social and Information Networks
Combinatorics
05C20, 05C38, 05C85, 05C90
This paper introduces the concepts of spectral influence and spectral cyclicality, both derived from the largest eigenvalue of a graph's adjacency matrix. These two novel centrality measures capture both diffusion and interdependence from a local and global perspective respectively. We propose a new clustering algorithm that identifies communities with high cyclicality and interdependence, allowing for overlaps. To illustrate our method, we apply it to input-output analysis within the context of the Moroccan economy.
title Spectral influence in networks: An application to Input-Output analysis
topic Social and Information Networks
Combinatorics
05C20, 05C38, 05C85, 05C90
url https://arxiv.org/abs/2305.02371