Resolution Limit in Community Detection¶
Fortunato, S., & Barthélemy, M. (2007). Resolution Limit in Community Detection. Proceedings of the National Academy of Sciences, 104(1), 36-41.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Partition Dependence of Aggregates
- The identical structural pattern appears in a macroeconomist's choice of accounting period (the same returns series mean-reverting at one period and momentum at another), a network scientist's choice of resolution parameter (four communities at one resolution and twenty at another), a redistricting commission's choice of boundaries (different partisan outcomes from the same voter distribution), and a clustering analyst's choice of K (different segment structures from the same database).
This sourceShows modularity optimization yields different module counts at different resolutions — the network instance of partition dependence.
Supported in partVerified against the work's full text
Fortunato and Barthelemy show modularity optimisation merges modules below a scale set by network size, but give no four-versus-twenty example and no macroeconomic, redistricting or K-choice cases.
“We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total size of the network”
- The identical structural pattern appears in a macroeconomist's choice of accounting period (the same returns series mean-reverting at one period and momentum at another), a network scientist's choice of resolution parameter (four communities at one resolution and twenty at another), a redistricting commission's choice of boundaries (different partisan outcomes from the same voter distribution), and a clustering analyst's choice of K (different segment structures from the same database).
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