Filter Bubbles

A filter bubble is a result state in which a website algorithm selectively guesses what information a user would like to see based on information about the user. This includes location, past click behavior, and search history. As a result, users can become separated from searched information that disagrees with their lives or viewpoints.

Information Hidden by Filter Bubbles


"In a TED Talk given around the time of the publication of The Filter Bubble, Pariser gave an illustration of how the filter bubble works. In the midst of the spring 2011 political protests in Egypt, he asked two friends to do a search in Google for "Egypt." One got a lot of information on the protests (not surprisingly), while the other got information on tourism in Egypt. Instead of this search providing results based on some objective, universally valid criteria-like PageRank in Google's early days-it was personalized to each user. Reflecting this search philosophy, Facebook founder Mark Zuckerberg has said that, '"A squirrel dying in front of your house may be more relevant to your interests right now than people dying in Africa."' (p. 1) People get different results from the same search, depending on what a search algorithm determines to be their individual interests and preferences. Perhaps touring the Nile and a dying squirrel might be more important to certain individuals at any one time than the fate of Africa. Is this the way we should organize Internet searching?" 1

Movements Against Filter Bubbles
There are many movements against search engines filtering information away from users. Many people feel slighted by having potential information filtered, and do not support having their search results modified because of their other online search or social activities. There are a couple organizations against filtering information on the internet:

is a guide by (see below) for escaping your search engine's filter bubble. Their alternative is using their search engine which will break you out of your filter bubble by default.

is an organization affiliated with Eli Pariser, the author of the New York Times Bestseller, The Filter Bubble. Their website informs users about how the filter bubble is used and what can be done about it.

Bursting the Filter Bubble
According to the MIT Technology Review, Eduardo Graells-Garrido, Mounia Lalmas, and Daniel Quercia at Yahoo Labs say that they have narrowed down a way to burst the filter bubble. Even though certain people have opposing views on sensitive topics, they may also share interests in other areas so they've built a recommendation engine that points these types of people towards each other based on their own preferences. The result of this is more or less a popping of the filter bubble, which provides users with a much wider range of opinions, ideas, and people than they would otherwise be in touch with. These developers believe that challenging people with new ideas makes them generally more receptive to change, which has important implications for social media websites. There has been some evidence that people sometimes become so against change that any type of redesign dramatically hinders the usage of that service. Giving these people a greater range of content in general could change those feelings. 2

“We conclude that an indirect approach to connecting people with opposing views has great potential,” say Graells-Garrido and co. 2

DuckDuckGo
is an internet search engine that uses information from many sources, such as crowdsourced websites like Wikipedia and from partnerships with other search engines like,  ,  , and  to obtain its results. It emphasizes protecting searchers' privacy and avoiding the filter bubble of personalized search results. It does not profile its users, and deliberately shows all users the same search results for a given query. Additionally, DuckDuckGo prioritizes results from the best sources, rather than from the majority of sources.