Using Social Network Analysis to Investigate the Potential of Innovation Networks: Lessons Learned from NASA's International Space Apps Challenge

Abstract

This research analyzes the affiliated multipartite social networks of hackathon style mass collaboration events. Using social network analysis we model the innovation networks for NASA's International Space Apps Challenge and use social network analysis to understand the structure of and relationships within the modeled networks. Using metrics such as degree, degree distribution, degree correlations, and density, the resulting models and study answer questions like: can social network statistics act as indicators of innovation performance within a network and which statistics provide insight to the likelihood of innovation performance? We address these research questions by building the affiliation networks for the 2012 and 2013 NASA International Space Apps Challenges and applying Gnyawali and Srivastava's conceptual model on cluster and network effects against these real-world networks to empirically prove the likelihood of innovation.