Network datasets
A collection of 40 large network datasets:
- Social networks: online social networks, edges represent interactions between people
- Communication networks: email communication networks with edges representing communication
- Citation networks: nodes represent papers, edges represent citations
- Collaboration networks: nodes represent scientists, edges represent collaborations (co-authoring a paper)
- Web graphs: nodes represent webpages and edges are hyperlinks
- Amazon networks : nodes represent products and edges link commonly co-purchased products
- Internet networks : nodes represent computers and edges communication
- Road networks : nodes represent intersections and edges roads connecting the intersections
Social networks
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| soc-Epinions1 | Directed | 75,879 | 508,837 | Who-trusts-whom network of Epinions.com |
| soc-LiveJournal1 | Directed | 4,847,571 | 6,8993,773 | LiveJournal online social network |
| soc-Slashdot0811 | Directed | 77,360 | 905,468 | Slashdot social network from November 2008 |
| soc-Slashdot0922 | Directed | 82,168 | 948,464 | Slashdot social network from February 2009 |
| wiki-Vote | Directed | 7115 | 103,689 | Wikipedia who-votes-on-whom network |
Communication networks
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| email-EuAll | Directed | 265,214 | 420,045 | Email network from a EU research institution |
| email-Enron | Directed | 36,692 | 367,662 | Email communication network from Enron |
| wiki-Talk | Directed | 2,394,385 | 5,021,410 | Wikipedia talk (communication) network |
Citation networks
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| cit-HepPh | Directed, Temporal, Labeled | 34,546 | 421,578 | Arxiv High Energy Physics paper citation network |
| cit-HepTh | Directed, Temporal, Labeled | 27,770 | 352,807 | Arxiv High Energy Physics paper citation network |
| cit-Patents | Directed, Temporal, Labeled | 3,774,768 | 16,518,948 | Citation network among US Patents |
Collaboration networks
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| ca-AstroPh | Undirected | 18,772 | 396,160 | Collaboration network of Arxiv Astro Physics |
| ca-CondMat | Undirected | 23,133 | 186,936 | Collaboration network of Arxiv Condensed Matter |
| ca-GrQc | Undirected | 5,242 | 28,980 | Collaboration network of Arxiv General Relativity |
| ca-HepPh | Undirected | 12,008 | 237,010 | Collaboration network of Arxiv High Energy Physics |
| ca-HepTh | Undirected | 9,877 | 51,971 | Collaboration network of Arxiv High Energy Physics Theory |
Web graphs
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| web-BerkStan | Directed | 685,230 | 7,600,595 | Web graph of Berkeley and Stanford |
| web-Google | Directed | 875,713 | 5,105,039 | Web graph from Google |
| web-NotreDame | Directed | 325,729 | 1,497,134 | Web graph of Notre Dame |
| web-Stanford | Directed | 281,903 | 2,312,497 | Web graph of Stanford.edu |
Product co-purchasing network
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| amazon0302 | Directed | 262,111 | 1,234,877 | Amazon product co-purchasing network from March 2 2003 |
| amazon0312 | Directed | 400,727 | 3,200,440 | Amazon product co-purchasing network from March 12 2003 |
| amazon0505 | Directed | 410,236 | 3,356,824 | Amazon product co-purchasing network from May 5 2003 |
| amazon0601 | Directed | 403,394 | 3,387,388 | Amazon product co-purchasing network from June 1 2003 |
Internet peer-to-peer networks
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| p2p-Gnutella04 | Directed | 10,876 | 39,994 | Gnutella peer to peer network from August 4 2002 |
| p2p-Gnutella05 | Directed | 8,846 | 31,839 | Gnutella peer to peer network from August 5 2002 |
| p2p-Gnutella06 | Directed | 8,717 | 31,525 | Gnutella peer to peer network from August 6 2002 |
| p2p-Gnutella08 | Directed | 6,301 | 20,777 | Gnutella peer to peer network from August 8 2002 |
| p2p-Gnutella09 | Directed | 8,114 | 26,013 | Gnutella peer to peer network from August 9 2002 |
| p2p-Gnutella24 | Directed | 26,518 | 65,369 | Gnutella peer to peer network from August 24 2002 |
| p2p-Gnutella25 | Directed | 22,687 | 54,705 | Gnutella peer to peer network from August 25 2002 |
| p2p-Gnutella30 | Directed | 36,682 | 88,328 | Gnutella peer to peer network from August 30 2002 |
| p2p-Gnutella31 | Directed | 62,586 | 147,892 | Gnutella peer to peer network from August 31 2002 |
Road networks
| Name | Type | Nodes | Edges | Description |
|---|---|---|---|---|
| roadNet-CA | Undirected | 1,965,206 | 5,533,214 | Road network of California |
| roadNet-PA | Undirected | 1,088,092 | 3,083,796 | Road network of Pennsylvania |
| roadNet-TX | Undirected | 1,379,917 | 3,843,320 | Road network of Texas |
Network types
- Directed : undirected network
- Undirected : directed network
- Bipartite : bipartite network
- Multigraph : network has multiple edges between a pair of nodes
- Temporal : for each node/edge we know when it appeared in the network
- Labeled : network contains labels (weights, attributes) on nodes and/or edges
Network statistics
| Dataset statistics | |
|---|---|
| Nodes | Number of nodes in the network |
| Edges | Number of edges in the network |
| Nodes in largest WCC | Number of nodes in the largest weakly connected component |
| Edges in largest WCC | Number of edges in the largest weakly connected component |
| Nodes in largest SCC | Number of nodes in the largest stongly connected component |
| Edges in largest SCC | Number of edges in the largest stongly connected component |
| Average clustering coefficient | Average clustering coefficient |
| Number of triangles | Number of triples of connected nodes (considering the network as undirected) |
| Fraction of closed triangles | Number of connected triples of nodes / number of length 2 paths |
| Diameter (longest shortest path) | Maximum shortest path length (sampled over 1,000 random nodes) |
| 90-percentile effective diameter | 90-th percentile of shortest path length distribution (sampled over 1,000 random nodes) |