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project_details.sh

$ cat graphlit-expansion.json

title: GraphLit ResearchRadar

category: ml

stack:Next.jsNeo4jPython/FastAPIForce-Directed GraphsGraph Algorithms

Force-directed 3D citation network visualization showing interconnected academic papers colored by research community

Project Overview

GraphLit ResearchRadar is a full-stack academic citation intelligence platform that maps 19,917 research papers across 42 thematic communities. The Python 3.14/FastAPI backend ingests paper metadata from the OpenAlex API via concurrent BFS expansion and stores the citation topology in a Neo4j graph database. The analytics engine runs Louvain community detection to identify research clusters and computes PageRank centrality, citation velocity, and predictive impact scores. A 4-signal hybrid collaborative filter (citation overlap, topic affinity, author collaboration, velocity) powers the personalized Neural Intelligence Feed. The Next.js 16 frontend renders interactive force-directed 2D/3D citation networks with physics simulation, hover-based adjacency highlighting, and directional particle flow. Server-side metadata generation provides dynamic SEO for all 19,917+ paper pages.