Jupyter Notebooks to Analyze Common Crawl Data

• analyzing data using the columnar index
  • blocking of internet connections from and to the Islamic Republic of Iran during the November 2019 crawl: net-blocking-iran-cc-main-2019-47.ipynb
  • total number of captures 2013 – 2019, domain coverage and approximation of unique URLs for the .edu top-level domain: cc-main-2013-2019-metrics.ipynb
  • correlations between character sets and lanuages: correlation-language-charset.ipynb
• analyze the Common Crawl webgraph data sets and interactively explore the graphs: cc-webgraph-statistics
• how to explore WARC files running a notebook on AWS EMR
• truncated record payloads in WARC Files:
  • verify that all truncated payloads are annotated by the WARC-Truncated header
  • which MIME types are mostly affected by truncation? Aggregations using the columnar index.