A filter bubble is a result of a personalized search in which the websites selectively guesses information a user would like to see based on the user's past activities and information on the web, for example, locations, past search history, past browsed websites, etc. As a result of filter bubbles, users usualy only see information that agrees with their own viewpoints. Two of the major and commonly seen example of filter bubbles are Google's Personalized Search, and Facebook's personalized news stream. Google's personalized search is closely associated with a browser cookie record -- not only it searches all the web pages to the search term, but also websites that the user visited for their previous search results. Facebook's personalized news stream acts in a similar way. It pushes and services contents that is, aligned with users' own ideology and greately replied on what users are choosing ant the content that are clicking. The Facebook News Feed caused some complaints among Facebook users, because it is considered too easy for users to track (how Data Privacy and Tracking works?) activities like changes in relationship status, events, and conversation with other users.