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Tutorials - Lucas Durand: Building an Interactive 🕸️ Network Graph 🕸️ to Understand Communities 👩🏽💻
Build interactive network graphs with Gephi to understand communities, social dynamics, and complex relationships using node and edge attributes, metrics, and visualization techniques.
- Interactive network graphs can be used to understand social dynamics and visualize complex relationships.
- Gephi is a popular open-source platform for network analysis and visualization.
- Node and edge attributes can be used to highlight specific features or behaviors in a network.
- Community detection algorithms can identify subgroups within a network based on similarity or other criteria.
- Network metrics such as centrality and clustering coefficient can provide insights into network structure and behavior.
- Visualizations such as node-link diagrams and force-directed layouts can be used to represent complex network topologies.
- Data preprocessing and cleaning are essential steps in network analysis to ensure accurate results.
- Network data can be sourced from various sources, including social media, email, or smartphone apps.
- Network analysis can be used in various fields, including social network analysis, epidemiology, and marketing.
- Python libraries such as NetworkX and Gephi-python can be used for network analysis and visualization.
- Node and edge labels can be used to provide additional context and meaning to network visualizations.
- Label propagation algorithms can be used to assign labels to nodes in a network based on their connections.