Mapping flows on weighted and directed networks with incomplete observations

Detecting significant community structure in networks with incomplete observations is challenging because the evidence for specific solutions fades away with missing data. For example, recent research shows that flow-based community detection methods can highlight spurious communities in sparse undi...

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Bibliographic Details
Published in:arXiv.org 2021-12
Main Authors: Smiljanić, Jelena, Blöcker, Christopher, Edler, Daniel, Rosvall, Martin
Format: Article
Language:English
Subjects:
Bayesian analysis
Flow mapping
Missing data
Networks
Online Access:Get full text
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Summary:Detecting significant community structure in networks with incomplete observations is challenging because the evidence for specific solutions fades away with missing data. For example, recent research shows that flow-based community detection methods can highlight spurious communities in sparse undirected and unweighted networks with missing links. Current Bayesian approaches developed to overcome this problem do not work for incomplete observations in weighted and directed networks that describe network flows. To address this gap, we extend the idea behind the Bayesian estimate of the map equation for unweighted and undirected networks to enable more robust community detection in weighted and directed networks. We derive a weighted and directed prior network that can incorporate metadata information and show how an efficient implementation in the community-detection method Infomap provides more reliable communities even with a significant fraction of data missing.
ISSN:2331-8422
DOI:10.48550/arxiv.2106.14798