Using Social Network Analysis to Understand NASA Collaborations

Social network work analysis allows evaluators to map and assess the relationships between people, groups, and organizations. In this paper we present the results of three years of social network analysis of the partnerships and collaborations from the NASA Earth Science Education Collaborative (NESEC). NESEC is a NASA SMD-funded cooperative that is working together towards the goal of enhancing STEM teaching and learning by creating engaging, meaningful, and authentic STEM experiences and resources. One of the goals of the collaborative is to work with strategic partners and collaborators to enhance earth science education in diverse learning environments. These collaborations and partnerships include those within the NASA Science Activation collective of education projects and external partners and collaborators.

Since the inception of the collaborative 2.5 years ago a yearly partnership survey has been deployed to understand how internal and external partners are collaborating and building relationships. The inclusion of a social network analysis in the examination of the survey data from years 1 and 2 helped to explain and demonstrate the pathways along which communication could happen but was not happening effectively and where communication was happening effectively. The social network analysis also showed that most external partners had a single, high-priority point of contact on the team. However, project documentation had not acknowledged the significant amount of effort those individuals needed to dedicate to sustaining those partnerships.

A year three survey will be deployed in late August 2018; this survey will repeat many of the questions from the previous surveys but will emphasize the strength of collaborations and partners between internal and external partners. These data will be analyzed using spatial-social network analysis techniques. This paper will reflect on how social network analysis and spatial-social network analysis techniques can be used to understand collaboration and partnership networks beyond the case presented.