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Buy Me a Coffee
This is the category text networks. It contains 10 networks. Text networks consist of text documents containing words. They are bipartite and their nodes are documents and words. Each edge represents the occurrence of a word in a document. Document types are for instance newspaper articles (TR) and Wikipedia articles (EX).
| Name | Attributes | n | m | Node meaning | Edge meaning |
| Daily Kos |   | 10,336 | 467,714 | Document, word | Occurrence |
| NIPS full papers | | 13,875 | 1,932,365 | Document, word | Occurrence |
| Reuters-21578 | | 60,234 | 1,464,182 | Article, word | Inclusion |
| Wikipedia words (en) |  | 276,739 | 7,846,807 | Article, word | Inclusion |
| Enron words | | 67,960 | 6,412,172 | Document, word | Occurrence |
| WebUni Magdeburg |  | 206,350 | 3,869,707 | Thread, word | Use |
| Reuters | | 1,065,176 | 96,903,520 | Story, word | Inclusion |
| NY Times | | 401,388 | 99,542,125 | Document, word | Occurrence |
| TREC (disks 4–5) | | 1,729,302 | 151,632,178 | Document, word | Inclusion |
| PubMed | | 8,341,043 | 737,869,083 | Document, word | Occurrence |