Change search
ReferencesLink to record
Permanent link

Direct link
The map equation
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.
Department of Biology, University of Washington.
2009 (English)In: The European Physical Journal Special Topics, ISSN 1951-6355, ISSN 1951-6401, Vol. 178, no 1, 13-23 p.Article in journal (Refereed) Published
Abstract [en]

Many real-world networks are so large that we must simplify their structure before we can extract useful information about the systems they represent. As the tools for doing these simplifications proliferate within the network literature, researchers would benefit from some guidelines about which of the so-called community detection algorithms are most appropriate for the structures they are studying and the questions they are asking. Here we show that different methods highlight different aspects of a network's structure and that the the sort of information that we seek to extract about the system must guide us in our decision. For example, many community detection algorithms, including the popular modularity maximization approach, infer module assignments from an underlying model of the network formation process. However, we are not always as interested in how a system's network structure was formed, as we are in how a network's extant structure influences the system's behavior. To see how structure influences current behavior, we will recognize that links in a network induce movement across the network and result in system-wide interdependence. In doing so, we explicitly acknowledge that most networks carry flow. To highlight and simplify the network structure with respect to this flow, we use the map equation. We present an intuitive derivation of this flow-based and information-theoretic method and provide an interactive on-line application that anyone can use to explore the mechanics of the map equation. We also describe an algorithm and provide source code to efficiently decompose large weighted and directed networks based on the map equation.

Place, publisher, year, edition, pages
2009. Vol. 178, no 1, 13-23 p.
National Category
Physical Sciences
URN: urn:nbn:se:umu:diva-36657DOI: 10.1140/epjst/e2010-01179-1OAI: diva2:355478
Available from: 2010-10-06 Created: 2010-10-06 Last updated: 2011-11-03Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Rosvall, MartinAxelsson, Daniel
By organisation
Department of Physics
In the same journal
The European Physical Journal Special Topics
Physical Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 29 hits
ReferencesLink to record
Permanent link

Direct link