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From: Dan Ream <dream@vcu.edu> Date: June 13, 2011 11:06:13 AM EDT To: web4lib@webjunction.org Cc: "McCulley, Lucretia" <lmcculle@richmond.edu> Subject: [Web4lib] Filter Bubbles and Libraries' Public Computers?

Web4Libers-

I've been reading and viewing with interest about Eli Pariser's book, "The Filter Bubble: What the Internet Is Hiding from You" and highly recommend his 9-minute TED talk summary about it at

http://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles.html (also on YouTube).

I don't recall this being discussed here before on Web4Lib, but if it has already, please point me to that discussion.

My questions concern how do the personalized search features that Google uses effect the shared public computers in our libraries. Beyond personal search history, Pariser estimates that Google uses 57 criteria to shape your results. Google hasn't publicly shared what those 57 are, but here's one search expert's guess..

http://www.rene-pickhardt.de/google-uses-57-signals-to-filter/

These are thought to include browser type, computer type, and many other factors that would seem chaotic, but influential to search results on a shared public computer in a library or campus computer lab.

Beyond the obvious difficulty this presents for teaching librarians to explain how Google results are found, I'm wondering what steps a library can take to reduce the personalization functions of Google so that your next Googler's search results aren't overly influenced by the twenty others who last sat at that same library workstation.

Thoughts or suggestions?

Dan Ream Director, Outreach and Distance Education Virginia commonwealth University Libraries Richmond, Virginia , USA

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