The New Gatekeepers: The role of algorithms in digital media by Tin Geber

Author:Tin Geber [Geber, Tin]
Language: eng
Format: mobi
Publisher: GitBook
Published: 2017-06-18T04:00:00+00:00

Explicit bias towards positive information limits exposure

Let’s turn our attention back to algorithm owners. The Facebook wall, i.e. the stream of news and updates on a user’s social connections, is algorithmically managed. To mitigate the signal to noise ratio and provide to users a subset of content that is cognitively manageable, Facebook uses algorithmic prioritization and assignment of weights to posts. One defining factor for automated parsing is positivity: posts that express gratitude, celebration, and positive sentiment in general hold more weight than posts that express sadness, rage, or negative sentiment. This phenomenon became obvious in 2014 after the incident in Ferguson, Missouri in the united States. Mike Brown, a black youth, was shot and killed by a white police officer seemingly without probable cause. Videos and eyewitness testimony show that Brown was kneeling, with his hands behind his head and his back turned to the police officer, when the police officer fired multiple shots, ending Brown’s life. This event sparked outrage in the black community and spread virally over the Internet on a number of social media — but not on Facebook. In fact, as Tufekci recounts,

Acting through computational agency, Facebook’s algorithm had “decided” that such stories did not meet its criteria for “relevance”—an opaque, proprietary formula that changes every week, and which can cause huge shifts in news traffic, making or breaking the success and promulgation of particular stories or even affecting whole media outlets. By contrast, Twitter’s algorithmically unfiltered feed allowed the emergence of millions of tweets from concerned citizens, which then brought the spotlight of the national media. Algorithmic filtering also by Twitter might have meant that a conversation about police accountability and race relations that has since shaken the country might never have made it out of Ferguson. (Tufekci, 2015, p. 213)

Twitter was the social media platform that let Ferguson reach critical mass and galvanize the public sphere. At the time, Twitter didn’t algorithmically manipulate its feed — all tweets from a user’s network were shown chronologically. Twitter was how news journalists got wind of the event and provided the amplifying effect that helped the #Ferguson phenomenon grow. If there was no Twitter, or if all social media news sharing platforms filtered their news algorithmically, there is a real possibility that Ferguson wouldn’t have turned into a highly important newsworthy event that spurred a new political activism movement, #BlackLivesMatter, highly active to this day across the United States in advocating for race equality.

From a financial standpoint, it makes sense for Facebook and similar platforms to filter for sentiment — we can safely assume that algorithm owners, if they run a for-profit venture, tweak the algorithms to maximize their profits. An obvious way of doing that is prioritising the types of posts that users on average are more willing to interact with, since higher levels of interaction mean more time spent on the platform, and an increased chance of viewing and interacting with advertising. This phenomenon does however suggest that algorithm owners fully control the chain

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