network-computation
CommunityCompute centrality, communities, and network visuals fast.
Data & Analytics#network visualization#network analysis#centrality#community detection#social networks#structural holes
Authorptreezh
Version1.0.0
Installs0
System Documentation
What problem does it solve?
It solves the problem of turning raw relational data into measurable social network insights and publication-ready visualizations.
Core Features & Use Cases
- Network construction & basics: Build networks from edge lists or adjacency matrices and compute core statistics like density, connectivity, and degree distributions.
- Centrality & community detection: Measure key nodes using degree/betweenness/closeness/PageRank-family metrics and detect communities with algorithms like Louvain or Girvan-Newman.
- Advanced diagnostics & graphs: Run structural hole analysis, small-world metrics, robustness checks, and generate clear network visualizations (including community coloring and dynamic network views).
Use case examples:
- Identify influential actors in an organization by computing multiple centrality measures.
- Detect and validate communication communities in a study dataset, then visualize community boundaries for reporting.
Quick Start
Ask the AI to compute centrality and community structure from your edge-list file, then produce a concise report and a visualization.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: network-computation Download link: https://github.com/ptreezh/sscisubagent-skills/archive/main.zip#network-computation Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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