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The Myth of The Algorithm: A System-Level View of Algorithmic Amplification | Knight First Amendment Institute

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A project studying algorithmic amplification and distortion, and exploring ways to minimize harmful amplifying or distorting effects Algorithmic recommender systems underlie much of the technology we interface with today, influencing everything from what products we buy, to what news sources or political viewpoints we’re exposed to, to how much income we earn from content that we create. In the context of social media, recent attention has turned to how these algorithmic systems can increase the reach of certain types of content relative to the reach they would have gotten under some other neutral baseline1 1. This definition is based on that given by Dean Eckles in testimony to the U.S. Congress. (Eckles 2021) —a phenomenon called “algorithmic amplification.” While the concept of algorithmic amplification could be applied to any type of content—for example, we could study the excess reach of cat memes on a platform—by and large, existing efforts to study, measure, or regulate algorith

Introduction Algorithmic recommender systems underlie much of the technology we interface with today, influencing everything from what products we buy, to what news sources or political viewpoints we're exposed to, to how much income we earn from content that we create. In the context of social media, recent attention has turned to how these algorithmic systems can increase the reach of certain types of content relative to the reach they would have gotten under some other neutral baseline 1 1. This definition is based on that given by Dean Eckles in testimony to the U.S. Congress. (Eckles 2021

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