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Today, Facebook’s data science team has put part of the “filter bubble” theory to the test and published the results in Science, a top peer-review scientific journal. Eytan Bakshy and Solomon Messing, two of the co-authors, were gracious enough to reach out and brief me at some length.
Each algorithm contains a point of view on the world. Arguably, that’s what an algorithm is: a theory of how part of the world should work, expressed in math or code. So while it’d be great to be able to understand them better from the outside, it’s important to see Facebook stepping into that conversation. The more we’re able to interrogate how these algorithms work and what effects they have, the more we’re able to shape our own information destinies.
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Here’s the upshot: Yes, using Facebook means you’ll tend to see significantly more news that’s popular among people who share your political beliefs. And there is a real and scientifically significant “filter bubble effect” — the Facebook news feed algorithm in particular will tend to amplify news that your political compadres favor.
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But it’s also not insignificant. For self-described liberals on Facebook, for example, the algorithm plays a slightly larger role in what they see than their own choices about what to click on. There’s an 8% decrease in cross-cutting content from the algorithm vs. a 6% decrease from liberals’ own choices on what to click. For conservatives, the filter bubble effect is about 5%, and the click effect is about 17% — a pretty different picture. (I’ve pulled out some .)
In the study, Bakshy, Messing, and Facebook data scientist Lada Adamic focused on the 10 million Facebook users who have labeled themselves politically. They used keywords to distinguish “hard news” content — about, say, politics or the economy — from “soft news” about the Kardashians. And they assigned each article a score based on the political beliefs of the people who shared it. If only self-described liberals shared an article, it was deemed highly liberal-aligned. (There are some caveats worth paying attention to on this methodology, which I highlighted below.)
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While this study focused on the first problem, it also offers some insight into the second, and the data there is concerning. Only 7% of the content folks click on on Facebook is “hard news.” That’s a distressingly small piece of the puzzle. And it suggests that “soft” news may be winning the war for attention on social media — at least for now.
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The conversation about the effects and ethics of algorithms is incredibly important. After all, they mediate more and more of what we do. They guide an increasing proportion of our choices — where to eat, where to sleep, who to sleep with, and what to read. From Google to Yelp to Facebook, they help shape what we know.
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