The progress of technology leaded us to have a convenience life nowadays. While the internet is being more common, our usage of internet also increased. We used plenty of time to react with internet everyday, searching different materials, browsing social medias, or finding information. The result or the information that we got form the internet doesn’t really come randomly as we think of. They all related to our habits, religious, and some more of our personal lives and this is named ‘filter bubble.’ “The filter bubble is the thing that controlling, for an example, the searching result on different searching engine so that it would be related to our interested.” (Pariser, 2012) It is a algorithm that ‘help’ us to determine what information is more suitable for us and this process is affecting on our usage of digital media.

Netflix will be the simplest example on explaining the filter bubble. “Netflix has around 1,000 people based in Silicon Valley who are charged with architecting the product and the personalization algorithm that resets every 24 hours to ensure users discover the exact content they want to watch out of an estimated 13,000 titles at any given time.” (Lara O’Reilly, 2016)  When you started up a Netflix account, Netflix will ask about some of your favorite shows. This action would help Netflix to know what’s your interest is and recommend some shows that related to your interest. Therefore, every time when log in to your Netflix homepage, you will see many different kinds of recommendations. This is one of the result of the filter bubble, only show the result that related to your interest and hiding the result that they don’t think you will like. This might be good for us sometimes since most of the time we would only watch our favorite types of shows. However, the filter bubble is not only appearing on the streaming media but some more others.

Social media have also been affected by the filter bubble. According to Tony Bradley, “Instagram have announced to start to filter the pictures in the user’s feed based on an algorithm.” (Bradley, 2016) This means that your Instagram feed will no long to be ordered by the time it posted but presented by the Instagram algorithm selection based on your ‘likes’ and following users and pages. This is not the first time that Instagram showing photos based on your interested. If you are an Instagram user, you might find out that the explore page that you have is different than the other users. This is because the explore of Instagram is grouped by your activity on Instagram which determined by the photos you ‘like’ the most. The action of Instagram maybe is benefiting user but the algorithm of photos or which photos to show should be determine by user themselves.

The arise of the filter bubble sometimes might good for our usage of internet since it only shows the things that we are interested in. However, we are not interested in doesn’t mean we want to know nothing of it. “We need to have some control to decide what gets through our digital media world and what doesn’t.” (Pariser, 2011) Everyone should have their own freedom on choose what to watch, to see, to receive but not by the algorithm or filter bubble. If our media resources keep organized by the system, “ultimately, web giants will be able to not only predict one’s interests and thinking, but shape it.” (Pariser, 2012) We shouldn’t let this happen because we should have the right to determine what is going to show to us in our own media world.

  1. Bradley, Tony. “Leave Me Out Of Your Instagram Algorithm Bubble.” Forbes. Forbes Magazine, 16 Mar. 2016. Web. 07 Mar. 2017. <https://www.forbes.com/sites/tonybradley/2016/03/16/leave-me-out-of-your-instagram-algorithm-bubble/#75b9c13663e5&gt;
  2. Pariser, Eli. The Filter Bubble : What the Internet Is Hiding from You. New York: Penguin, 2011. Print.
  3. Pariser, Eli. Beware Online Filter Bubble’” TED. Mar. 2012. Lecture.

  4. O’Reilly, Lara. “Netflix lifted the lid on how the algorithm that recommends you titles to watch actually works.” Business Insider. Business Insider, 26 Feb. 2016. Web. 07 Mar. 2017. <http://www.businessinsider.com/how-the-netflix-recommendation-algorithm-works-2016-2&gt;.
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