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Convener in chief:


David Lazer
(Methodology, Networked Governance)

Editors:


Stanley Wasserman
(Current Trends, Methodology, Social Networks)

Guy Stuart
(Economic Sociology, Finance)

David Gibson
(Social Networks, Interaction, Theory)

Allan Friedman
(Simulations)

Jukka-Pekka Onnela
(Methodology, Social Networks, Technology)

Nathan Eagle
(Technology, Social Computing, Powerlaws, Current Trends)

Ben Waber
(Technology, Social Computing)
Ines Mergel
(Knowledge Sharing, Social Computing, Social Software, Government 20)

Maria Binz-Scharf
(Qualitative Methodology, Knowledge Sharing, eGovernment)

Alexander Schellong
(Admin, eGovernment, Government 20, Citizen Relationship Management)

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« Upcoming "Workshop on Information in Networks" | Main | Future Networks Conference at MIT »

21 September 2009

Communities in Networks

Uncovering the "community" structure of social networks has a long history, but communities play a pivotal role in almost all networks across disciplines. Intuitively, one can think of a network community as consisting of a group of nodes that are relatively densely connected to each other but sparsely connected to other dense groups of nodes. Communities are important because they are thought to have a strong bearing on functional units in many networks. So, for example, communities in social networks can correspond to different social groups, such as family, whereas web pages dealing with a given subject tend to form topical communities.

The concept is simple enough, but it turns out that coming up with precise mathematical definitions and algorithms for community detection is one of the most challenging problems in network science. Recently, a lot of the research in this area has been done using ideas from statistical physics, which has an arsenal of tools and concepts to tackle the problem. Unfortunately (but understandably) relatively few non-physicists like to read statistical physics papers.

Together with my colleagues Mason Porter (Oxford University) and Peter Mucha (University of North Carolina at Chapel Hill), we thought it would be useful to let others take a peek at some of this work. In an effort to put in context some of the hundreds of papers, we recently compiled an introductory review on some of our favorite approaches to community detection. While there are excellent existing reviews, our "Communities in Networks", published by Notices of the American Mathematical Society (AMS), tries to make sense of this smorgasbord of methods and, hopefully, lets a broader audience get a flavor of this exciting field.

I hope to be making a couple of postings on community structure and community detection later on. In the meantime, you can see for yourself if we have succeeded by checking out the freely accessible article on the AMS website, or by going to arXiv or SSRN.

community.gif
The largest connected component of a coauthorship network connecting physicists who have published together on networks. Each node is colored according to community membership.

Posted by JP Onnela at September 21, 2009 9:40 AM