This project is an interactive network analysis of George R.R. Martin's A Song of Ice and Fire (Book 1), exploring how fictional character interactions mirror real-world sociopolitical systems. Built with R's igraph and visNetwork packages, the presentation maps characters as nodes and their textual proximity (co-occurrence within 15 words) as weighted edges to visualize the political landscape of Westeros. Key features of the analysis: Interactive Visualization: Renders a dynamic node-link graph where node size reflects character influence (degree centrality) and color represents distinct political factions. Community Detection: Uses the Louvain algorithm to identify structural social clusters, verifying that mathematically derived communities align with the story's actual noble houses. Structural Validation: Compares the fictional network's clustering coefficients, average path lengths, and degree distributions against known metrics for real-world social networks. Sociological Insights: Demonstrates that the novel exhibits scale-free and small-world properties, proving the author constructed a mathematically realistic model of human connectivity and power dynamics.

This notebook is a small, intended-to-be reproducible slice of that arc applied to sustainable finance. This uses R to structure and visualize a few things from two bank climate-risk reports, that apparently changed how I think.