Network Analysis Libraries
Libraries for analyzing network structures and discovering patterns in connected data.
Supported Solution Fields
When to Use
- When analyzing network topology
- When finding communities
- When measuring centrality
- When detecting clusters
When Not to Use
- When data isn't networked
- When simple metrics suffice
- When visualization is primary need
Tradeoffs
- Algorithm Choice vs Speed: More complex algorithms take longer
- Scale vs Memory: Larger networks need more resources
- Accuracy vs Performance: Better results need more computation
Commercial Implementations
-
NetworkX
- Python library for complex networks
- Comprehensive algorithms
- Research standard
-
igraph
- High-performance graph analysis
- Multiple language support
- Visualization capabilities
Common Combinations
- Social network analysis
- Citation networks
- Infrastructure mapping
Case Study: Research Network Analysis
A university analyzed research collaboration networks:
Challenge
- Complex collaboration patterns
- Multiple disciplines
- Temporal evolution
Solution
- Implemented NetworkX
- Community detection
- Centrality analysis
Results
- Identified key collaborators
- Improved research planning