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October 22, 2024

Host- and Domain-Level Web Graphs August, September, and October 2024

Note: this post has been marked as obsolete.
We are pleased to announce a new release of host-level and domain-level Web Graphs based on the crawls of August, September, and October 2024. The crawls used to generate the graphs were CC-MAIN-2024-33, CC-MAIN-2024-38, and CC-MAIN-2024-42.
Thom Vaughan
Thom Vaughan
Thom is Principal Technologist at the Common Crawl Foundation.

We are pleased to announce a new release of host-level and domain-level Web Graphs based on the crawls of August, September, and October 2024. The crawls used to generate the graphs were CC-MAIN-2024-33, CC-MAIN-2024-38, and CC-MAIN-2024-42. Additional information about the data formats, the processing pipeline, our objectives, and credits can be found in the announcements of prior Web Graph releases. You may also visit the projects cc-webgraph and cc-pyspark which include all scripts and tools required to construct the graphs. Instructions to explore the graphs in the webgraph format are given in our collection of Web Graph Notebooks.

Host-level Graph

The host-level graph consists of 299.9 million nodes and 2.6 billion edges.

There are 238.2 million dangling nodes (79.44%) and the largest strongly connected component contains 40.8 million (13.61%) nodes. Dangling nodes stem from:

  • Hosts that have not been crawled, yet are pointed to from a link on a crawled page
  • Hosts without any links pointing to a different host name
  • Hosts which did only return an error page (eg. HTTP 404).

Host names in the graph are in reverse domain name notation and a leading www. is stripped: www.subdomain.example.com becomes com.example.subdomain.

You can download the graph and the ranks of all 299.9 million hosts from AWS S3 on the path s3://commoncrawl/projects/hyperlinkgraph/cc-main-2024-aug-sep-oct/host/ (this requires an account on AWS). Alternatively, you can use https://data.commoncrawl.org/projects/hyperlinkgraph/cc-main-2024-aug-sep-oct/host/ as prefix to access the files from everywhere.

Please note that the text representation of the host-level graph is shipped in 48 gzip-compressed files listed in two path listings - one for the nodes (vertices), one for the edges (arcs). First, download the paths listing and decompress it using "gzip -d" or "gunzip". By adding the prefix s3://commoncrawl/ or https://data.commoncrawl.org/ to each line in the path listing you get the list of URLs to download the entire graph.

Download files of the Common Crawl August, September, October 2024 host-level Web Graph

Size File Description
175 Bytes cc-main-2024-aug-sep-oct-host-vertices.paths.gz nodes ⟨id, rev host⟩, paths of 16 vertices files
215 Bytes cc-main-2024-aug-sep-oct-host-edges.paths.gz edges ⟨from_id, to_id⟩, paths of 32 edges files
5.3 GiB cc-main-2024-aug-sep-oct-host.graph graph in BVGraph format
1.3 KiB cc-main-2024-aug-sep-oct-host.properties
5.4 GiB cc-main-2024-aug-sep-oct-host-t.graph transpose of the graph (outlinks inverted to inlinks)
1.3 KiB cc-main-2024-aug-sep-oct-host-t.properties
816 Bytes cc-main-2024-aug-sep-oct-host.stats WebGraph statistics
5.1 GiB cc-main-2024-aug-sep-oct-host-ranks.txt.gz harmonic centrality and pagerank

Domain-level Graph

The domain graph is built by aggregating the host graph on the level of pay-level domains (PLDs) based on the public suffix list maintained on publicsuffix.org. Version (commit) e637219 of the public suffix list was used (commit date 2024-10-22T07:30:21Z).

The domain-level graph has 96.0 million nodes and 1.7 billion edges. 52.0% or 50.0 million nodes are dangling nodes, the largest strongly connected component covers 33.7 million or 35.12% of the nodes.

All files related to the domain graph are available on AWS S3 under s3://commoncrawl/projects/hyperlinkgraph/cc-main-2024-aug-sep-oct/domain/ or on https://data.commoncrawl.org/projects/hyperlinkgraph/cc-main-2024-aug-sep-oct/domain/.

Download files of the Common Crawl August, September, October 2024 domain-level Web Graph

Credits

Thanks to the authors of the WebGraph framework, whose software made the computation of graph properties and ranks possible. We hope the data will be useful for you to do any kind of research on ranking, graph analysis, link spam detection, etc.

Let us know about your results via our Discord Server or Google Group.

This release was authored by:
Thom is Principal Technologist at the Common Crawl Foundation.
Thom Vaughan