Community Structure Characterization
arXiv:1705.10621 · doi:10.1007/978-1-4614-7163-9_110151-1
Abstract
This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry.
References in corpus (11)
- Fast unfolding of communities in large networks
- Modularity and community structure in networks
- Maps of random walks on complex networks reveal community structure
- Community detection in networks: A user guide
- Quantifying social group evolution
- An information-theoretic framework for resolving community structure in complex networks
- Characterizing the community structure of complex networks
- GED: the method for group evolution discovery in social networks
- Community Evolution of Social Network: Feature, Algorithm and Model
- Interpreting communities based on the evolution of a dynamic attributed network
- A community role approach to assess social capitalists visibility in the Twitter network