Social Network Analysis

Obsidian plugin for analyzing the social networks within your knowledge base using graph theory metrics and visualization.

Features

• Multiple Centrality Measures: Degree, Betweenness, Eigenvector, Closeness, PageRank, and Harmonic centrality
• Clustering Analysis: Calculate clustering coefficients to identify communities
• Weighted Links: Optional link weighting based on mention frequency
• Directional Analysis: Analyze backlink direction in your graph
• Auto-Export: Automatically export analysis results to markdown files (currently broken)
• Interactive UI: View results in a dedicated panel with sortable metrics

Quick Start (Users)

Installation

1. Navigate to your Obsidian vault's plugins folder: .obsidian/plugins/

   • If it doesn't exist, enable "Community plugins" in Settings and click the folder icon next to "Installed plugins"

2. Clone this repository into the plugins folder:

   cd .obsidian/plugins
   git clone https://github.com/fiddlestix27/Obsidian-SNA.git
   

That's it! The plugin is ready to use.

Development Setup (Contributors)

If you want to modify the plugin, follow these steps:

Setup

1. Clone the repository into your development folder (development within the actual plugins folder is not recommended):

   cd <repository-development-folder>
   git clone https://github.com/fiddlestix27/Obsidian-SNA.git obsidian-sna
   cd obsidian-sna
   

2. Install dependencies:

   npm install
   

Making Changes

1. Make your desired changes

2. Remove the current main.js file

3. Recompile the plugin:

   npm run build
   

   Or for development with watch mode:

   npm run dev
   

4. Restart Obsidian to see your changes

The recompiled main.js will be generated automatically.

Usage

Opening the Plugin

• Use the command palette (Cmd/Ctrl + P) and search for "Social Network Analysis"
• Or use the sidebar icon

Analyzing Your Graph

1. Open the Graph view in Obsidian (Ctrl/Cmd + G)
2. In the Social Network Analysis panel, click "Analyze Graph"
3. View results for all centrality measures
4. Export results with the "Export Results" button

Available Commands

• Open: Open the SNA panel
• Analyze Graph: Run analysis on your current graph
• Calculate Centrality Measures: Compute all centrality metrics
• Export Results: Save results to a markdown file

Settings

Graph Analysis Options

• Enable Directional Analysis: Consider backlink direction (default: ON)
• Enable Weighted Links: Weight edges by mention frequency (default: ON)
• Enable Clustering: Calculate clustering coefficients (default: ON)
• Layout Algorithm: Choose from force-directed, hierarchical, or circular (default: force-directed)
• Minimum Link Weight: Filter links below this threshold (default: 1)
• Auto-Export Results: Automatically save results after analysis (default: OFF) - currently broken

Individual Metrics

Toggle individual centrality measures on/off:

• Closeness Centrality
• Betweenness Centrality
• Eigenvector Centrality
• PageRank
• Harmonic Centrality

Centrality Measures Explained

Degree Centrality

Number of direct connections each node has. Nodes with high degree centrality are hubs in your network.

Betweenness Centrality

Measures how often a node appears on shortest paths between other nodes. High betweenness indicates a node that bridges different parts of your graph.

Eigenvector Centrality

Importance based on connections to other important nodes. A node is important if it connects to other important nodes.

Closeness Centrality

Average distance to all other nodes. Nodes with high closeness are well-integrated into the network.

PageRank

Probability of reaching a node through random walk. Useful for identifying "hub" notes that many others link to.

Harmonic Centrality

Sum of reciprocals of distances to all other nodes. A more robust alternative to closeness centrality.

Clustering Coefficient

Measures how much neighbors of a node are connected. High clustering indicates tight-knit communities.

System Requirements

• Obsidian 1.7.2 or higher
• Node.js 24+ (for development/building from source)
• npm (for development/building from source)

Performance

The plugin is optimized for networks up to 5,000+ nodes. For very large graphs, analysis may take several seconds depending on your hardware.

Troubleshooting

Plugin won't load

• Ensure manifest.json, main.js, and styles.css are in the plugin folder
• Restart Obsidian
• Check Obsidian console for error messages (Settings → About → Open debug console)

No graph data found

• Open the Graph view first (Ctrl/Cmd + G)
• Ensure your vault has linked notes
• Try clicking "Analyze Graph" again

Analysis is slow

• Try reducing the number of enabled metrics in settings
• Close other resource-intensive plugins
• Limit analysis to a subset of your graph if possible

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run npm run build to recompile
5. Submit a pull request

License

GNU GPL v3 License

Support

For issues, feature requests, or questions:

• Open an issue on GitHub

Good plugins to integrate with this

https://github.com/elsatam/obsidian-extended-graph

https://github.com/mafgin/obsidian-graph-heatmap

https://github.com/moonweave/obsidian-graph-styler

https://github.com/obsidianmd/obsidian-importer - automated data import from csv or other formats, maintained by Obsidian themselves. Great if you want to perform SNA on large datasets.

Changelog

v1.0.0

• Initial release
• All core centrality measures implemented
• Interactive UI panel
• Settings and customization
• Auto-export functionality

v1.1.0

• Updated dependencies to latest stable releases
• Added eslint.config.mjs for cleaner linting
• Awaited updates:
  • layout customization
  • narrow by path or grouping (adjust SNA calculations by current view)
  • left vs right eigenvector specifications when directional analysis is enabled
  • fix auto export