Abstract
Social Network Analysis (SNA) is a methodological approach that measures and assess relational patterns across a network of individuals or groups. This research demonstrates how SNA can reveal the structure of relational networks within intellectually diverse and geographically distant research teams, and how these network structures can influence team capacity and research outcomes. SNA is a powerful tool with which to quantitatively measure structural patterns of connection and disconnection across a network, as well as the potential influence individuals derive from their position within the network structure. Understanding how the structure of large research collaborations contribute to research outcomes is vital to generating feedback that informs integration processes and the resultant conversations surrounding scientific collaboration. These insights are critical to the success of interdisciplinary initiatives at the institutional, state, and national level, and arguably provide insight to multi-institutional initiatives at a global scale.