Compressing strongly connected subgroups in social networks: An entropy-based approach |
| |
Authors: | Dominic Brenner Andreas Dellnitz Wilhelm Rödder |
| |
Institution: | 1. FernUniversit?t in Hagen, Center of Logistics, Hagen, Germany;2. FernUniversit?t in Hagen, Department of Operations Research, Hagen, Germany |
| |
Abstract: | To detect and study cohesive subgroups of actors is a main objective in social network analysis. What are the respective relations inside such groups and what separates them from the outside. Entropy-based analysis of network structures is an up-and-coming approach. It turns out to be a powerful instrument to detect certain forms of cohesive subgroups and to compress them to superactors without loss of information about their embeddedness in the net: Compressing strongly connected subgroups leaves the whole net’s and the (super-)actors’ information theoretical indices unchanged; i.e., such compression is information-invariant. The actual article relates on the reduction of networks with hundreds of actors. All entropy-based calculations are realized in an expert system shell. |
| |
Keywords: | Entropy graph compression information theory network analysis social networks |
|
|