| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 537.28 KB | Adobe PDF |
Advisor(s)
Abstract(s)
In social network analysis the identification of communities and the
discovery of brokers is a very important issue. Community detection typically
uses partition techniques. In this work the information extracted from social
networking goes beyond cohesive groups, enabling the discovery of brokers
that interact between communities. The partition is found using a set covering
formulation, which allows the identification of actors that link two or more
dense groups. Our algorithm returns the needed information to create a good
visualization of large networks, using a condensed graph with the identification
of the brokers.
Description
Keywords
Data mining Graph mining Condensed network Brokerage Social networks
Citation
Publisher
Springer