The last 15 years, users of the Wayback Machine have browsed past versions of websites by entering in URLs into the main search box and clicking on Browse History. With the generous support of , we’re adding an exciting new feature to this search box: keyword search!
With this new beta search service, users will now be able to find the home pages of over 361 Million websites preserved in the Wayback Machine just by typing in keywords that describe these sites (e.g. “new york times”). As they type keywords into the search box, they will be presented with a list of relevant archived websites with snippets containing:
Instant results as you type — predictive, interactive and speedy
Multilingual
Search in any language or using symbols — expanding scope and utility
Limit results to certain websites or domains using the site: operator
Search index was built by processing over 250 billion webpages archived over 20 years
Index contains more than a billion terms whatsapp lead collected from over 400 billion hyperlinks to the homepages of websites
Search results are ranked based on the number of relevant hyperlinks to the site’s homepage and the total number of web captures from the site
Example queries
Websites related to academic journals — academic journals
Searching in Greek to find websites related to Aristotle — Αριστοτέλειο
Government websites related to climate change — site:gov climate change
Stanford websites related to Asian studies — site:stanford.edu asian studies
We hope that this service, to search and discover archived web resources through time, will create new opportunities for scholarly work and innovation.
A big Thank You to: Vinay Goel, Kenji Nagahashi, Mark Graham, Bill Lubanovic, John Lekashman, Greg Lindahl, Vangelis Banos, Richard Caceres, Zijian He, Eugene Krevenets, Benjamin Mandel, Rakesh Pandey, Wendy Hanamura and Brewster Kahle
Have you ever wondered what happened to all the GIF animations that sparkled in the dawn of the internet? According to artists Greg Niemeyer and Olya Dubatova, they have become part of the digital subconscious, and the Berkeley Art Museum & Pacific Film Archive (BAMPFA) is presenting what that subconscious might look like, in an exhibit called GIF Collider.
Niemeyer studied both the Internet Archive’s collections of GIF animations and the Prelinger Film Archives from the 1950’s. He noticed how the film archives, which include ads, educational films and propaganda, show a heavy gender and racial bias. In comparison, the GIF animations from forty years later reflect less gender and racial bias—but we can’t help but wonder with more historical distance, what kinds of bias will become apparent in the future.