Wednesday, October 28, 2015
Thursday, October 1, 2015
What is a Filter Bubble and Could This be Why Your Aunty Shares Crazy Stuff on Facebook...?
As a librarian, I love Google.
Google is amazing.
I find and learn amazing stuff via Google...
Have you ever wondered, though, in a Google ubiquitous world, how it is that your Aunties and old high school classmates can end up sharing such bizarre, crazy stuff on Facebook?
It actually probably has a lot to do with the personalization of search. Did you know there is no such thing as a "standard" Google search? Beginning back in about 2009, Google began using your personal search history and approximately 57 other "click indicators" to personalize the results lists you see when you run a search. That means that when you search for "Egypt" from your house in Manoa, you probably see a very different set of results than your Aunty Lulu sees when she searches for "Egypt" from her house in rural Maine.
The web is a big place. The idea that we aren't all seeing the same parts of the web even when we search for the same terms on the same tools is the main concept behind what Eli Pariser has termed a "filter bubble."
It's not just Google either. Facebook, Instagram, Yahoo, Bing... Social media and much of search has become personalized through the use of software algorithms.
Though Eli Pariser presented this Ted Talk back in 2011, the ideas and caveats behind algorithmic filter bubbles are more relevant than ever.
Next post: How we begin to help students venture beyond their filter bubbles...
Google is amazing.
I find and learn amazing stuff via Google...
Have you ever wondered, though, in a Google ubiquitous world, how it is that your Aunties and old high school classmates can end up sharing such bizarre, crazy stuff on Facebook?
It actually probably has a lot to do with the personalization of search. Did you know there is no such thing as a "standard" Google search? Beginning back in about 2009, Google began using your personal search history and approximately 57 other "click indicators" to personalize the results lists you see when you run a search. That means that when you search for "Egypt" from your house in Manoa, you probably see a very different set of results than your Aunty Lulu sees when she searches for "Egypt" from her house in rural Maine.
The web is a big place. The idea that we aren't all seeing the same parts of the web even when we search for the same terms on the same tools is the main concept behind what Eli Pariser has termed a "filter bubble."
It's not just Google either. Facebook, Instagram, Yahoo, Bing... Social media and much of search has become personalized through the use of software algorithms.
Though Eli Pariser presented this Ted Talk back in 2011, the ideas and caveats behind algorithmic filter bubbles are more relevant than ever.
Next post: How we begin to help students venture beyond their filter bubbles...
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