Community Structure in Time-Dependent, Multiscale and Multiplex Networks [ Via Science ]

This morning I participated in the first set panels at the Duke Political Networks Conference.  Our panel was entitled “Dynamic Networks.”  On the panel was Peter Mucha from UNC-Math, who presented Community Structure in Time-Dependent, Multiscale, and Multiplex Networks [Mucha, Richardson, Macon, Porter, Onnela].

Suffice to say, this is a very exciting paper.   Indeed, the paper is in this week’s edition of Science Magazine.  The article fills an important hole in the broader literature and I believe the approach outlined therein will be adopted by many scholars.

Here is the abstract: “Network science is an interdisciplinary endeavor, with methods and applications drawn from across the natural, social, and information sciences. A prominent problem in network science is the algorithmic detection of tightly connected groups of nodes known as communities. We developed a generalized framework of network quality functions that allowed us to study the community structure of arbitrary multislice networks, which are combinations of individual networks coupled through links that connect each node in one network slice to itself in other slices. This framework allows studies of community structure in a general setting encompassing networks that evolve over time, have multiple types of links (multiplexity), and have multiple scales.”

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