Article companion

What these are

These notebooks accompany the survey article Community Detection with the Map Equation and Infomap: Theory and Applications (doi:10.1145/3779648), section by section. They are more academic and article-aligned than the rest of this site. For a gentler, Python-first path, start with the chapters: Concepts, Working with Infomap, Flow models, Workflows, and Robustness. Treat these notebooks as deeper companion reading.

The notebooks live in the Infomap repository under examples/notebooks/ and are numbered to match the survey’s sections. Some require additional research code or data-processing packages and are not executed as part of this documentation.

Foundations

Higher-order representations

Metadata, bipartite, and incomplete data

Applications

Not yet covered by a narrative chapter

These four application topics do not have a dedicated chapter on this site yet. For now, the companion notebooks below are the best Python starting point.

Citing this work

If you use Infomap, cite the 2008 PNAS paper and the MapEquation software package; see How to cite Infomap. To cite the survey itself, use doi:10.1145/3779648.