Leveraging Information Theory & Graph Theory to Monitor Communication Networks in Team Settings

Effective communication is a critical component of successful collaboration in group projects and team settings. However, tracking and analyzing these communications can be challenging, especially in complex, multi-member teams such as those found in the Aerospace Industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy and applying Ecological Network Analysis techniques, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the first 14 weeks of the project. This research aims to answer the question “How does Project COMET’s communication structure evolution during the first three months of the project mirror food web evolution (from immature to mature ecosystems)?” Graph theory is used to represent communication structures, identify key nodes, information bottlenecks, and interaction patterns. The findings show that most ENA metrics, including Ascendency, Robustness, Generalization/Vulnerability, Number of Links, Number of Actors, Total System Throughflow, and Total System Overhead/Normalized Overhead were consistent with other research and evolved over time as expected. This work provides a key first step towards a new, in-situ approach to influential members and detect potential communication gaps. We seek to help quantify and provide insights into key performance indicators like team dynamics, collaboration efficiency, and adaptive strategies for observing information flow in team structures. In the long term, this research aims to lay the foundation for the advancement of structured communication tracking and improved teamwork in educational and professional environments.