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Social Network Analysis Visualization NetworkX & Plotly Community Detection Open Source

Social Network Analysis Visualization with NetworkX and Plotly for network graphs, community detection, centrality measures, and interactive network exploration. Complete implementation with interactive 2D/3D network graphs, community detection (Louvain algorithm), centrality measures (Degree, Betweenness, Closeness, Eigenvector, PageRank), network metrics dashboard, edge analysis, shortest path visualization, subgraph extraction, network generation (random, scale-free, small-world, complete, star, ring, grid, community networks), path analysis, key node identification, network resilience analysis, network comparison, and data export (CSV, JSON, PNG, PDF, SVG, HTML). Perfect for analyzing relationships, network structures, social networks, and graph analysis. Features 1 comprehensive Jupyter notebook and 6 Python modules for network analysis.

Network Graphs NetworkX Community Detection Centrality Measures Download Now Path Analysis Network Metrics Get Started
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Social Network Analysis Visualization with NetworkX and Plotly Project - RSK World
Social Network Analysis Visualization with NetworkX and Plotly Project - RSK World
Network Visualization Network Analysis Python NetworkX Plotly Graph Theory

This project creates comprehensive social network analysis visualizations using NetworkX and Plotly. It includes interactive 2D/3D network graphs, community detection (Louvain algorithm), centrality measures (Degree, Betweenness, Closeness, Eigenvector, PageRank), network metrics dashboard, edge analysis, shortest path visualization, subgraph extraction, network generation (random, scale-free, small-world, complete, star, ring, grid, community networks), path analysis, key node identification, network resilience analysis, network comparison, and data export (CSV, JSON, PNG, PDF, SVG, HTML). The project provides user-friendly interface for network analysis and visualization with 1 comprehensive Jupyter notebook and 6 Python modules for network analysis. Features include interactive graphs, community detection, centrality analysis, and comprehensive network analysis tools.

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Interactive Network Graphs

Create beautiful, interactive 2D and 3D network graphs with Plotly. Interactive zoom, pan, and hover functionality with customizable node sizes, colors, edge widths, and layout algorithms.

  • 2D and 3D network visualizations
  • Interactive zoom, pan, and hover
  • Customizable styling and colors
  • Multiple layout algorithms

Community Detection

Automatic community detection using the Louvain algorithm. Visualize communities with color-coded nodes, analyze community sizes and structures, and extract subgraphs.

  • Louvain algorithm implementation
  • Color-coded community visualization
  • Community statistics analysis
  • Subgraph extraction

Centrality Measures (5 Types)

Comprehensive centrality analysis including Degree, Betweenness, Closeness, Eigenvector, and PageRank centralities. Identify key nodes and influential network members.

  • Degree, Betweenness, Closeness
  • Eigenvector and PageRank
  • Side-by-side comparison visualizations
  • Key node identification

Network Metrics Dashboard

Comprehensive network metrics including density, clustering coefficient, degree distribution, network size, and visual gauge charts for key metrics.

  • Network density calculations
  • Clustering coefficient analysis
  • Degree distribution histograms
  • Visual metrics dashboard

Edge Analysis

Detailed edge analysis with edge weights visualization, edge betweenness calculation, color-coded edge importance, and hover information for edges.

  • Edge weights visualization
  • Edge betweenness calculation
  • Color-coded edge importance
  • Interactive edge hover information

Path Analysis

Find and visualize shortest paths between nodes, calculate average path length, network diameter, and comprehensive path statistics.

  • Shortest path finding
  • Path visualization
  • Average path length calculation
  • Network diameter analysis

Subgraph Extraction

Extract custom subgraphs based on node selection or community membership. Visualize subgraphs within full network context and analyze independently.

  • Custom subgraph extraction
  • Community subgraph extraction
  • Subgraph visualization
  • Independent subgraph analysis

Network Generation (8 Types)

Generate various network types including random (Erdos-Renyi), scale-free (Barabasi-Albert), small-world (Watts-Strogatz), complete, star, ring, grid, and community networks.

  • Random and scale-free networks
  • Small-world networks
  • Complete, star, ring, grid networks
  • Community-structured networks

Network Comparison

Compare multiple networks side-by-side with metrics comparison, statistical analysis, and export comparison results to CSV.

  • Side-by-side network comparison
  • Metrics comparison
  • Statistical analysis
  • Export comparison results

Key Node Identification

Identify most important nodes by various centrality measures. Find influential nodes, bridge nodes, and hub nodes in the network.

  • Top nodes by centrality
  • Influential node identification
  • Bridge node detection
  • Hub node analysis

Network Resilience Analysis

Test network resilience by removing nodes (random or targeted), track network fragmentation, and measure network robustness metrics.

  • Node removal testing
  • Random and targeted removal
  • Component analysis
  • Resilience metrics

Data Export

Export network analysis results to CSV, JSON, and export visualizations as PNG, PDF, SVG, or interactive HTML files.

  • CSV and JSON data export
  • PNG, PDF, SVG image export
  • Interactive HTML export
  • Edge list export

Data Loading

Load networks from CSV files with support for various data formats. Save networks to CSV files for data persistence.

  • CSV network import
  • CSV network export
  • Multiple format support
  • Data validation

Network Statistics

Comprehensive network statistics including connectedness analysis, component analysis, and statistical summaries of network properties.

  • Comprehensive metrics calculation
  • Connectedness analysis
  • Component analysis
  • Statistical summaries

Jupyter Notebook

Comprehensive tutorial with 1 Jupyter notebook covering network analysis basics, community detection, centrality measures, path analysis, and advanced features demonstration.

  • network_analysis.ipynb - Main analysis
  • Interactive exploration
  • Step-by-step examples
  • All features demonstrated

Requirements

The following are the technical requirements for this project:

  • Python 3.8+
  • NetworkX 3.0+
  • Plotly 5.17.0+
  • Pandas 2.0.0+
  • NumPy 1.24.0+
  • Jupyter Notebook 1.0.0+
  • kaleido 0.2.1+ (optional)
  • scipy 1.10.0+
  • matplotlib 3.7.0+
  • python-louvain 0.16+

Credits & Acknowledgments

This project is developed for educational purposes and utilizes the following resources:

  • Python - PSF License
  • NetworkX - BSD License
  • Plotly - MIT License
  • Pandas - BSD License
  • RSK World - Project Inspiration
  • GitHub Repository - Source code and documentation

Support & Contact

For paid applications, please contact us for integration help or feedback.

  • Support Email: help@rskworld.in
  • Contact Number: +91 9330539277
  • Website: RSKWORLD.in
  • GitHub Project
  • Join Our Discord
  • Slack Support Channel
  • Network Analysis Documentation
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Categories

Network Visualization Network Analysis Python NetworkX Plotly Graph Theory

Technologies

Python 3.8+
NetworkX
Plotly
Network Analysis
Graph Theory

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About RSK World

Founded by Molla Samser, with Designer & Tester Rima Khatun, RSK World is your one-stop destination for free programming resources, source code, and development tools.

Founder: Molla Samser
Designer & Tester: Rima Khatun

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