skills.rest
ptreezh
ptreezhCOMMUNITY
Explore all skills by this author →
GitHub

performing-centrality-analysis

Compute degree, closeness, betweenness, and eigenvector centrality from JSON network input.

24|7|Updated Nov 15, 2025
Search Tags:#networkx#betweenness#social networks#centrality analysis#key node identification#eigenvector centrality
One-click install
npx skills add https://github.com/ptreezh/sscisubagent-skills --skill performing-centrality-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performing-centrality-analysis
Source: https://github.com/ptreezh/sscisubagent-skills/tree/main/archive/skills/analysis/performing-centrality-analysis
Command: npx skills add https://github.com/ptreezh/sscisubagent-skills --skill performing-centrality-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires networkx, pandas, numpy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you quantify and interpret key nodes in a social network so you can understand power centers, information bottlenecks, and influence structure rather than relying on intuition.

Core Features & Use Cases

  • Four centrality metrics: computes degree, closeness, betweenness, and eigenvector centrality to capture different notions of “importance”.
  • Key-node identification: classifies hubs (degree), bridges (betweenness), and influencers (eigenvector) using threshold rules.
  • Research-context interpretation: supports Chinese social-network framing (e.g., guanxi/relationships) to help explain what the numbers mean in practice.

Use case: You have a network of actors in an organization or collaboration graph and need to identify which individuals are central connectors, fast information spreaders, and influential figures for a research write-up.

Quick Start

Run the centrality pipeline by telling an AI: compute all four centrality measures for network.json and output centrality.json with the top 20 nodes for each chosen metric.

Frequently Asked Questions about performing-centrality-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute centrality measures to identify key nodes in a social network?▼

To compute centrality measures for key node identification, provide a JSON network input to calculate degree, closeness, betweenness, and eigenvector centrality, yielding a standardized multi-metric JSON output for ranking nodes.

What is the difference between betweenness and eigenvector centrality for influencer identification?▼

Betweenness centrality identifies information bridges by measuring shortest-path frequency, while eigenvector centrality identifies influencers by scoring nodes connected to other highly connected nodes within the social network.

Can I use networkx with pandas for organizational network studies and centrality analysis?▼

Yes, you can use networkx with pandas and numpy for organizational network studies, computing centrality metrics from relationship data to classify hubs, bridges, and influencers using threshold-based categorization.

How do I rank top nodes by centrality threshold rules in a complex graph?▼

Rank top nodes by applying threshold-based key-node categorization to centrality scores, classifying hubs via degree, bridges via betweenness, and influencers via eigenvector centrality to output ranked JSON results.

Does this centrality analysis pipeline support matplotlib for visualizing actor-relationship networks?▼

Yes, the centrality analysis pipeline includes matplotlib as a dependency, supporting visualization of actor-relationship networks alongside the computed multi-metric centrality JSON output for organizational network studies.

Related Skills

Explore More Data & Analytics Skills→
ptreezhptreezh
24

network-computation-expert

Transform social relationship data into networks and compute centrality and community detection results.

Community
Advanced
Zeyuyang-0420Zeyuyang-0420

networkx

Create, manipulate, and analyze complex networks with Python libraries.

Community
Advanced
LogauaEngstromLogauaEngstrom
18

networkx

Model complex relationships as graphs and compute network metrics with NetworkX.

Community
Advanced
ptreezhptreezh
24

network-computation

Build graphs from relational inputs and compute centrality and community detection.

Community
Intermediate