What makes certain groups of people catalyze disproportionate creative or scientific output? This project, funded by the John Templeton Foundation, takes a data-driven approach to identifying and understanding inspirational cohorts—clusters of individuals whose collective interactions spark transformative ideas.
Combining network science, natural language processing, and large language models, the project pursues three interconnected goals: (1) mapping the structure and dynamics of inspirational communities across history, (2) understanding how cultural and institutional contexts shape the emergence of these cohorts, and (3) applying the Science of Purpose framework to uncover how shared purpose drives collective achievement.
By analyzing large-scale data on collaboration, co-location, and intellectual exchange, this research aims to reveal the network signatures that distinguish inspirational cohorts from ordinary groups, offering insights into how to cultivate environments that foster breakthrough innovation.