Filter Bubble
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A Filter Bubble is the isolation or dilution of outside information by algorithms. An ethnocentric environment is facilitated when algorithms return content based on assumed user relevance. In turn, users are less exposed to opposing viewpoints and steer towards content that echoes reflect ethnocentric ideologies[1]. The term first appeared in Eli Pariser's novel Filter Bubble, where he noted how personalization is changing the web and the dangers of becoming isolated in one's own beliefs[2].
Recent political campaigns have pushed filter bubble's into mainstream discourse. Some argue they are a driving factor behind upset political victories, such as Brexit and Trump's campaign [3]. ocial media rely on a relevance based algorithm to sort displayed content[4]. For the first time ever, 62% of American adults receive their news from social media[5]. As media platforms, these sites control the flow of information and political discourse, isolating users in their own cultural or ideological convictions. This became apparent in the Wall Street Journal's article titled "Red Feed, Blue Feed"[6].
Abstract
The goal of a relevance algorithm is to learn a user's preferences in order to curate content on their feed. This allows a feed to be personalized, being unique depending on the user. Microsoft researcher Tarleton Gillespie explains, "navigate massive databases of information, or the entire web. Recommendation algorithms map our preferences against others, suggesting new or forgotten bits of culture for us to encounter. Algorithms manage our interactions on social networking sites, highlighting the news of one friend while excluding another's. Algorithms designed to calculate what is 'hot' or 'trending' or 'most discussed' skim the cream from the seemingly boundless chatter that's on offer. Together, these algorithms not only help us find information, they provide a means to know what there is to know and how to know it, to participate in social and political discourse, and to familiarize ourselves with the publics in which we participate"[7]. This style of curation fosters user engagement and activism within the site. The concept has a snowballing effect, as more user activism teaches the algorithm to better select content. Soon, the cycle isolates a user. While seeming harmless, when this concept is drawn across political ideologies, it can hinder a person's ability to see alternative points of view. In Stanford University's overview of democracy, a citizen must "listen to the views of other people" and reminds people not to be "so convinced of the rightness of your views that you refuse to see any merit in another position. Consider different interests and points of view"[8]. Thus, to facilitate a constructive democracy, it is important to recognize alternative views.
Social Media as News Media Platforms
Quotes
“Your computer monitor is a kind a one-way mirror, reflecting your own interests while algorithmic observers watch what you click.” ― Eli Pariser[9]
References
- ↑ http://www.npr.org/sections/alltechconsidered/2016/07/24/486941582/the-reason-your-feed-became-an-echo-chamber-and-what-to-do-about-it
- ↑ https://www.youtube.com/watch?v=SG4BA7b6ORo
- ↑ https://www.theguardian.com/media/2017/jan/08/eli-pariser-activist-whose-filter-bubble-warnings-presaged-trump-and-brexit
- ↑ https://cs.illinois.edu/sites/default/files/files2/sigir11_cwang.pdf
- ↑ http://www.journalism.org/2016/05/26/news-use-across-social-media-platforms-2016/
- ↑ "Red Feed, Blue Feed"
- ↑ http://www.tarletongillespie.org/essays/Gillespie%20-%20The%20Relevance%20of%20Algorithms.pdf "The Relevance of Algorithms"
- ↑ https://web.stanford.edu/~ldiamond/iraq/WhaIsDemocracy012004.htm "What is Democracy?"
- ↑ The Filter Bubble: What the Internet is Hiding From You
More to come. [Kennedy Kaufman]
