Graphs, Networks and Python: The Power of Interconnection
summary
Uses the NetworkX Python library to build a real email graph from a TSV of Enron mail and claims the full import of 300000 emails 80000 recipients runs on a two‑year‑old laptop in about a second. Constructs undirected graphs, directed digraphs, and multi‑graphs that store each message as a separate edge (message body can live on the edge). Extracts top‑degree nodes, builds subgraphs, exports to export to GEXF and visualize in Gephi, and warns clique finding is NP‑complete and can be very slow.
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chapters (23)
- 0:00Intro
- 0:36A little about me...
- 9:02Lets add some edges
- 9:21Lets Visualise it
- 10:09Now a directed graph
- 10:48Look Ma - No Nodes
- 12:16More Graphs
- 13:04Erdos-Renyi
- 15:36Watts-Strogatz
- 16:48Barabasi - Albert
- 19:46Social Network Analyis
- 20:27Enron Data
- 22:45Load the email data
- 22:55Build the graph
- 23:54And visualise!!!
- 25:26Node Degree
- 27:16The People
- 28:08Subgraphs
- 30:28MultiGraphs
- 31:39Relationships?
- 33:54Networkx Functionality
- 34:46Other useful graph Packages
- 35:48Conclusion
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