Collaboration Networks Analysis: Combining Structural and Keyword-based Approaches

Year: 2017
Venue: Semantic Keyword-Based Search on Structured Data Sources
Product of the Action: Yes

Keystone Members Authors:

This paper proposes a framework for the analysis of the characteristics of collaboration networks. The framework uses social network analysis metrics which are especially applicable to directed and weighted collaboration networks. By using the proposed framework it is possible to investigate the global structure of the collaboration networks, such as density, centralisation, assortativity and the dynamics of network growth. Furthermore, the framework proposes appropriate network centrality measures (degree and its variations for directed and weighted networks) for ranking the nodes. In addition the proposed framework combines a keyword-based approach and Louvain algorithm for the community detection task. Next, the paper describes a case study in which the proposed framework is applied to the collaboration networks emerged from STSMs on the KEYSTONE COST Action.