Network Operations and Internet Security @ UChicago

Bobble “Filter Bobble” Tool Released

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We have released Bobble, a Chrome extension to help users visualize how their search results are being personalized.  The filter bubble is a concept developed by Internet activist Eli Pariser to describe a phenomenon where websites use algorithms to predict what information a user may like to see based on the user’s location, search history, etc. As a result, a website may only show information which agrees with the user’s viewpoints. One such example is Google’s personalized search results. To “pop” the bubbles created by Google search (also called de-personalization), we have developed Bobble, a Chrome extension that uses hundreds of nodes to distribute a user’s Google search queries worldwide each time the user performs a Google search.

Author: Nick Feamster

Nick Feamster is a professor in the Department of Computer Science at Princeton University. Before joining the faculty at Princeton, he was a professor in the School of Computer Science at Georgia Tech. He received his Ph.D. in Computer science from MIT in 2005, and his S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT in 2000 and 2001, respectively. His research focuses on many aspects of computer networking and networked systems, including the design, measurement, and analysis of network routing protocols, network operations and security, and anonymous communication systems. In December 2008, he received the Presidential Early Career Award for Scientists and Engineers (PECASE) for his contributions to cybersecurity, notably spam filtering. His honors include the Technology Review 35 "Top Young Innovators Under 35" award, a Sloan Research Fellowship, the NSF CAREER award, the IBM Faculty Fellowship, and award papers at SIGCOMM 2006 (network-level behavior of spammers), the NSDI 2005 conference (fault detection in router configuration), Usenix Security 2002 (circumventing web censorship using Infranet), and Usenix Security 2001 (web cookie analysis).

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