What problem does it solve?
This Skill helps you turn historical correspondence and prosopographic records into analyzable networks, then quantify how relationships, influence, and communities change over time despite archival incompleteness.
Core Features & Use Cases
- Correspondence Network Construction: Build directed multigraphs from sender–recipient letter datasets (preserving one edge per letter, with year/doc_id attributes).
- Temporal Network Metrics: Compute decade-window betweenness centrality to identify intermediaries/brokers and track their rise or decline over time.
- Prosopography-Enriched Graphs: Attach historical person attributes (name, title, gender, institution, lifespans) to network nodes for interpretation.
- Community Detection & Persistence: Run Louvain community detection per time window and measure community stability across periods via Jaccard similarity.
- Gephi Visualization Export: Export an annotated graph to GEXF (including node attributes and edge weights) for interactive exploration in Gephi.
Quick Start
Use the historical-network skill to build a decade-window correspondence graph from your CSV, compute temporal betweenness, detect Louvain communities per decade, and export the annotated network to a Gephi-ready GEXF file.
