alterlab-sna

name	alterlab-sna
description	Applies social-network-analysis method discipline to relational data — degree/betweenness/closeness/eigenvector centrality and PageRank, community detection (Louvain and greedy-modularity native in networkx, Leiden via igraph), and inferential network models (ERGM) — choosing the measure that matches the substantive question and the right dependence assumptions, then routing computation to the existing networkx (and igraph/R) tooling. Use when the request mentions social network analysis, centrality, key players/brokerage, community or cluster detection in a network, ERGM, or modeling ties between nodes. For general graph algorithms and plotting prefer alterlab-networkx; for graph neural networks prefer alterlab-torch-geometric. Part of the AlterLab Academic Skills suite.
license	MIT
allowed-tools	Read Bash(python:*)
compatibility	Computation routes to networkx>=3.4 (centrality, native Louvain/greedy-modularity). Leiden and very large graphs -> python-igraph>=0.11. ERGM has no mature Python package -> R statnet/ergm via an R bridge (declare it). No API key; runs locally via `uv run python`.
metadata	{"skill-author":"AlterLab","version":"1.0.0","depends_on":"alterlab-networkx (computation), alterlab-ssci-design-gate; audited by alterlab-ssci-inference-gate"}

Social Network Analysis — Match the Measure to the Question

Skill type: ANALYSIS MODULE. SNA treats the ties as the data. The discipline is not running a centrality function — it is choosing the centrality that answers the substantive question, respecting network dependence (ties are not independent observations), and using an inferential model (ERGM) when you want to explain tie formation rather than describe it. Computation is handed to alterlab-networkx.

Core Mission

THE TIE IS THE UNIT. PICK THE CENTRALITY THAT MATCHES THE QUESTION; TIES ARE NOT IID.

When to Use This Skill

• "Run a social network analysis / compute centrality on my network."
• "Who are the key players / brokers in this network?"
• "Detect communities / clusters in my network."
• "Fit an ERGM to explain why ties form."

Does NOT Trigger

The request is really about…	Route to	Why not this skill
General graph algorithms / plotting / I/O	alterlab-networkx	This skill adds SNA method choice; networkx executes.
Graph neural networks / node embeddings for prediction	alterlab-torch-geometric	Deep learning on graphs, not SNA description/inference.
Whether a relational design is appropriate	alterlab-ssci-design-gate	Design routing, upstream.
Plain tabular statistics	alterlab-statistical-analysis	No network structure.

Centrality — pick by the substantive claim (verified networkx 3.x)

Question	Centrality	Call
Who has the most direct ties?	degree	nx.degree_centrality(G)
Who bridges otherwise-separate groups?	betweenness (brokerage)	nx.betweenness_centrality(G)
Who can reach everyone fastest?	closeness	nx.closeness_centrality(G)
Who is connected to well-connected others?	eigenvector / PageRank