References

The papers behind the methods in these chapters, collected in one place. Each chapter cites the relevant ones inline and links the matching survey-companion notebook under its “Going deeper” heading. For how to cite Infomap itself, see Citing Infomap.

[ARL18]

Ulf Aslak, Martin Rosvall, and Sune Lehmann. Constrained information flows in temporal networks reveal intermittent communities. Physical Review E, 97(6):062312, 2018. doi:10.1103/PhysRevE.97.062312.

[Bas59]

Georgii P. Basharin. On a statistical estimate for the entropy of a sequence of independent random variables. Theory of Probability & Its Applications, 4(3):333–336, 1959.

[BHM+22]

Aleix Bassolas, Anton Holmgren, Antoine Marot, Martin Rosvall, and Vincenzo Nicosia. Mapping nonlocal relationships between metadata and network structure with metadata-dependent encoding of random walks. Science Advances, 8(43):eabn7558, 2022. doi:10.1126/sciadv.abn7558.

[BGLL08]

Vincent D. Blondel, Jean-Loup Guillaume, Renaud Lambiotte, and Etienne Lefebvre. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10):P10008, 2008. doi:10.1088/1742-5468/2008/10/P10008.

[BlockerR20]

Christopher Blöcker and Martin Rosvall. Mapping flows on bipartite networks. Physical Review E, 102(5):052305, 2020. doi:10.1103/PhysRevE.102.052305.

[CBMN+19]

Joaquín Calatayud, Rubén Bernardo-Madrid, Magnus Neuman, Alexis Rojas, and Martin Rosvall. Exploring the solution landscape enables more reliable network community detection. Physical Review E, 100(5):052308, 2019. doi:10.1103/PhysRevE.100.052308.

[DDLAR15]

Manlio De Domenico, Andrea Lancichinetti, Alex Arenas, and Martin Rosvall. Identifying modular flows on multilayer networks reveals highly overlapping organization in interconnected systems. Physical Review X, 5(1):011027, 2015. doi:10.1103/PhysRevX.5.011027.

[ETC+24]

Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson. From local to global: a graph rag approach to query-focused summarization. arXiv preprint arXiv:2404.16130, 2024. doi:10.48550/arXiv.2404.16130.

[EBR17]

Daniel Edler, Ludvig Bohlin, and Martin Rosvall. Mapping higher-order network flows in memory and multilayer networks with infomap. Algorithms, 10(4):112, 2017. doi:10.3390/a10040112.

[EHR26]

Daniel Edler, Anton Holmgren, and Martin Rosvall. The MapEquation software package. https://mapequation.org, 2026.

[EM19]

Scott Emmons and Peter J. Mucha. Map equation with metadata: varying the role of attributes in community detection. Physical Review E, 100(2):022301, 2019. doi:10.1103/PhysRevE.100.022301.

[ECL+22]

Anton Eriksson, Timoteo Carletti, Renaud Lambiotte, Alexis Rojas, and Martin Rosvall. Flow-based community detection in hypergraphs. In Higher-Order Systems, pages 141–161. Springer, Cham, 2022. doi:10.1007/978-3-030-91374-8_4.

[EER+21]

Anton Eriksson, Daniel Edler, Alexis Rojas, Manlio de Domenico, and Martin Rosvall. How choosing random-walk model and network representation matters for flow-based community detection in hypergraphs. Communications Physics, 4:133, 2021. doi:10.1038/s42005-021-00634-z.

[FBarthelemy07]

Santo Fortunato and Marc Barthélemy. Resolution limit in community detection. Proceedings of the National Academy of Sciences, 104(1):36–41, 2007. doi:10.1073/pnas.0605965104.

[HER23]

Anton Holmgren, Daniel Edler, and Martin Rosvall. Mapping change in higher-order networks with multilevel and overlapping communities. Applied Network Science, 8:42, 2023. doi:10.1007/s41109-023-00565-4.

[KR15]

Tatsuro Kawamoto and Martin Rosvall. Estimating the resolution limit of the map equation in community detection. Physical Review E, 91(1):012809, 2015. doi:10.1103/PhysRevE.91.012809.

[KLR16]

Masoumeh Kheirkhahzadeh, Andrea Lancichinetti, and Martin Rosvall. Efficient community detection of network flows for varying markov times and bipartite networks. Physical Review E, 93(3):032309, 2016. doi:10.1103/PhysRevE.93.032309.

[LR12]

Renaud Lambiotte and Martin Rosvall. Ranking and clustering of nodes in networks with smart teleportation. Physical Review E, 85(5):056107, 2012. doi:10.1103/PhysRevE.85.056107.

[NSmiljanicR25]

Magnus Neuman, Jelena Smiljanić, and Martin Rosvall. Reliable data clustering with bayesian community detection. arXiv preprint arXiv:2510.15013, 2025. doi:10.48550/arXiv.2510.15013.

[PBER16]

Christian Persson, Ludvig Bohlin, Daniel Edler, and Martin Rosvall. Maps of sparse markov chains efficiently reveal community structure in network flows with memory. arXiv preprint arXiv:1606.08328, 2016. doi:10.48550/arXiv.1606.08328.

[RAB09]

Martin Rosvall, Daniel Axelsson, and Carl T. Bergstrom. The map equation. The European Physical Journal Special Topics, 178(1):13–23, 2009. doi:10.1140/epjst/e2010-01179-1.

[RB08]

Martin Rosvall and Carl T. Bergstrom. Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105(4):1118–1123, 2008. doi:10.1073/pnas.0706851105.

[RB11]

Martin Rosvall and Carl T. Bergstrom. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems. PLoS ONE, 6(4):e18209, 2011. doi:10.1371/journal.pone.0018209.

[REL+14]

Martin Rosvall, Alcides V. Esquivel, Andrea Lancichinetti, Jevin D. West, and Renaud Lambiotte. Memory in network flows and its effects on spreading dynamics and community detection. Nature Communications, 5:4630, 2014. doi:10.1038/ncomms5630.

[Sha48]

Claude E. Shannon. A mathematical theory of communication. The Bell System Technical Journal, 27(3):379–423, 1948. doi:10.1002/j.1538-7305.1948.tb01338.x.

[SmiljanicBlockerE+26]

Jelena Smiljanić, Christopher Blöcker, Daniel Edler, Anton Holmgren, Magnus Neuman, Alexis Rojas, and Martin Rosvall. Community detection with the map equation and infomap: theory and applications. ACM Computing Surveys, 2026. doi:10.1145/3779648.

[SmiljanicBlockerER21]

Jelena Smiljanić, Christopher Blöcker, Daniel Edler, and Martin Rosvall. Mapping flows on weighted and directed networks with incomplete observations. Journal of Complex Networks, 9(6):cnab044, 2021. doi:10.1093/comnet/cnab044.

[SmiljanicER20]

Jelena Smiljanić, Daniel Edler, and Martin Rosvall. Mapping flows on sparse networks with missing links. Physical Review E, 102(1):012302, 2020. doi:10.1103/PhysRevE.102.012302.

[SZLP16]

Laura M. Smith, Linhong Zhu, Kristina Lerman, and Allon G. Percus. Partitioning networks with node attributes by compressing information flow. ACM Transactions on Knowledge Discovery from Data, 2016. doi:10.1145/2968451.

[TWvE19]

Vincent A. Traag, Ludo Waltman, and Nees Jan van Eck. From louvain to leiden: guaranteeing well-connected communities. Scientific Reports, 9:5233, 2019. doi:10.1038/s41598-019-41695-z.