A substantial volume of research has been devoted to studies of community structure in networks, but communities are not the only possible form of large-scale network structure. Here we describe a broad extension of community structure that encompasses traditional communities but includes a wide range of generalized structural patterns as well. We describe a principled method for detecting this generalized structure in empirical network data and demonstrate with real-world examples how it can be used to learn new things about the shape and meaning of networks.
- Computer Science - Social and Information Networks, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Statistical Mechanics, Physics - Data Analysis, Statistics and Probability, Physics - Physics and Society, Statistics - Machine Learning
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Mathematics and Algorithms for Data (MAD)
- Department of Mathematical Sciences - Visiting Reader
Person: Research & Teaching, Honorary / Visiting Staff