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.
Missing link observations in weighted and directed networks aggravate this overfitting problem since each link carries more information.
To address this problem, here 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 that an efficient implementation in the community-detection method Infomap provides more reliable communities even with a significant fraction of the data missing.
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