WebKB Texas WebKB (GCN Benchmark)

A WebKB texas dataset of 187 web pages, 298 hyperlinks, collected by Yang et al. (ICML 2016). Each record contains web page features, hyperlink edges, class labels. WebKB texas university web page classification dataset. Suitable for node classification, web page categorization, graph neural networks.

#Benchmark graph#Graph neural network#Node classification#University web page

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Analytics

The interactive network needs JavaScript.

· graph.json

Node size is centrality, colour is community. Hover a node for details; click one to isolate its community.

187
Nodes
298
Edges
1.71e-02
Density
4
Components
-0.2621
Assortativity
0.0%
Reciprocity
80
Bridges
Most central nodes
1250.5591
90.0914
1670.06989
80.05376
10.04839
1010.04839
1120.04839
1450.04839
1160.04301
280.04301
Content metrics

187 records scored · min–maxmean ± 0.675 σ (the interquartile range if the values are roughly normal)mean

labelavg 1.58 / 4
0std 0.914
feature countμ 82.551 ± 47.789
min 15max 433
is test10.2% true
true 10.2%false 89.8%
4.4
Flesch–Kincaid grade
US school grade level
3.6
Automated readability index
Frequent terms
142151115257228365397270154390496236114549389149181328292376649126252325120152295386557294109116342417141272433237483303310130201226739121243135210341

Computed over the full corpus.

Record

Catalog key
gcn_webkb_texas
Authors
Craven, Mark; DiPasquo, Dan; Freitag, Dayne; McCallum, Andrew; Mitchell, Tom; Nigam, Kamal; Slattery, Seán
Year
2000
Source paper
Learning to construct knowledge bases from the World Wide Web
DOI / arXiv
10.1016/s0004-3702(00)00004-7
License
Academic Use (LicenseRef-Research-Only)
Records
187
Nodes
187
Edges
298
Nodes are
web page
Edges are
hyperlink
Attributes
nodes have no attributes; edges have no attributes
Languages
en
Collected
2016 (2010s)
Tasks
Node classification (multi-class; label) inferred
From the graph: link prediction, community detection
Region
Global (inferred: the platform is used worldwide)

Provenance

Originally published at
https://github.com/kimiyoung/planetoid link checked
Hosted copy
Mirrored on echo.directory on 2026-10-09, 17.2 MB across 80 files. Checksums in MANIFEST.json.

Citations

Learning to construct knowledge bases from the World Wide Web
M. Craven, Dan DiPasquo, Dayne Freitag, Andrew Mccallum, Tom Michael Mitchell
Journal Article · Artificial Intelligence · 2000

565
citations
well cited
27
influential citations
5% of all citations

Cited by

Show all 10

Citation data from Semantic Scholar, retrieved 2026-10-22.

How to cite

BibTeX

@misc{echo2026,
  title  = {ECHO: Exploratory Compendium of Humanity Online},
  author = {Switzer, Braden and Zafarani, Reza},
  year   = {2026},
  url    = {https://echo.directory},
  note   = {Syracuse University}
}

@article{Craven_2000,
  title     = {Learning to construct knowledge bases from the World Wide Web},
  volume    = {118},
  issn      = {0004-3702},
  url       = {http://dx.doi.org/10.1016/s0004-3702(00)00004-7},
  doi       = {10.1016/s0004-3702(00)00004-7},
  number    = {1-2},
  journal   = {Artificial Intelligence},
  publisher = {Elsevier BV},
  author    = {Craven, Mark and DiPasquo, Dan and Freitag, Dayne and McCallum, Andrew and Mitchell, Tom and Nigam, Kamal and Slattery, Seán},
  year      = {2000},
  month     = Apr,
  pages     = {69–113}
}

APA

Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory

Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., & Slattery, S. (2000). WebKB Texas WebKB (GCN Benchmark) [Data set]. https://doi.org/10.1016/s0004-3702(00)00004-7

MLA

Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.

Craven, Mark, et al. WebKB Texas WebKB (GCN Benchmark). 2000, doi.org/10.1016/s0004-3702(00)00004-7.

BibTeX · RIS · CSL-JSON

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