Team Members: Jilan Lang, Shen Zhou, Yunfan Gong, Mingzhe Liu
KOAA-AAS wants to measure, document, and visualize how the total solar eclipse has impacted the Rochester community network. Therefore, the goal of this project was to understand shifts in sub-community dynamics and changes in interactions within the Rochester community. To achieve this goal, students applied the Louvain Algorithm, a distance-based community detection method, to divide the Rochester network into six sub-communities and assigned descriptive keywords to each sub-community. They also employed advanced visualization techniques to analyze and transformed data, quantifying changes both within and between these sub-communities. The team’s results highlighted the impact of the total eclipse on the Rochester community, showcasing how interactions and relationships evolved over time. This project provided a clear picture of the broader societal and cultural effects of the eclipse, how significant astronomical events can alter community behavior and engagement patterns.