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Publications
  • Shah, Chirag. What Do You Look Like on YouTube? Politics Magazine. July 2009. [Online]
  • Shah, Chirag. TubeKit - A Query-based YouTube Crawling Toolkit. In Bulletin of IEEE Technical Committee on Digital Libraries, 5(1), Spring 2009. [Online]
  • Marchionini, Gary, Shah, Chirag, Lee, Christopher A., Capra, Robert. Query Parameters for Harvesting Digital Video and Associated Contextual Information. In the Proceedings of JCDL 2009. June 15-19, 2009. Austin, Texas.
  • Shah, Chirag. Supporting Research Data Collection from YouTube with TubeKit. In the Proceedings of YouTube and the 2008 Election Cycle in the United States. April 16-17, 2009. Amherst, MA. (3rd prize)
  • Shah, Chirag. TubeKit - A Query-based YouTube Crawling Toolkit. Demo at JCDL 2008.
  • Capra, Robert, Lee, Christopher A., Marchionini, Gary, Russell, Terrell, Shah, Chirag, and Stutzman, Fred. Selection and Context Scoping for Digital Video Collections: An Investigation of YouTube and Blogs. In JCDL 2008.
  • Shah, Chirag and Marchionini, Gary. Preserving 2008 US Presidential Election Videos. In the Proceedings of International Web Archiving Workshop (IWAW) 2007.
Talks (by Chirag Shah)
  • Supporting Research Data Collection from YouTube with TubeKit. At YouTube and the 2008 Election Cycle in the United States Conference. April 16, 2009. Amherst, MA. [Talk]
  • Republic of Web: A web of, by, and for the people. CRADLE talk. UNC Chapel Hill. November 14, 2008. [Slides in PDF]
  • We, the People on YouTube: Understanding Democracy of, by, and for the Online Media Sharing. University Research Day Talk. UNC Chapel Hill. March 4, 2008.
  • Hunting for Hip, Hipsters, and Happenings on YouTube - A ContextMiner Story. CRADLE Talk. UNC Chapel Hill. September 21, 2007.
  • Finding Connectors, Mavens, and Salesmen on YouTube. Yahoo! Research Berkeley, CA. August 10, 2007.
  • Preserving 2008 US Presidential Election Videos. International Web Archiving Workshop (IWAW) 2007. Vancouver, BC, Canada. June 23, 2007.
Related Projects
  • ContextMiner: a general framework to collect contextual information for digital objects.
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