Paper short abstract:

This paper outlines a theory of fake news by amplification. It argues that the networked circulation process that results from these acts of amplification can best be understood through their similarity to digital contemporary legends.

Paper long abstract:

To some, "Fake News" is a question of truth—a term that refers to purposely untrue stories that spread informally across networks and can be empirically disproven by facts. To others, "Fake News" means bias—a discrediting label hurled at media that disagrees with your viewpoint. This paper suggests a reorientation that looks at fake news not only in terms of "truth" or "bias" but also based on belief.

This paper outlines a theory of fake news by amplification. "Amplification" occurs when news or events become amplified beyond their importance due to the affordances of networks. A few users tweeting rapidly may produce a trending hashtag; a few partisan blog posts may be picked up by television news and given mainstream credibility as a "controversy." Problematically, amplification leads to distortion. As stories become amplified over networks, they lose important context, like the size of the controversy or whether something began as a joke. This distortion only increases as stories spread and users add new context or interpretations based on existing worldviews and media narratives.

I argue that the networked circulation process resulting from this amplification can best be understood through its similarity to digital contemporary legends. Like legends, these stories aren't made up wholesale—they are based on real people and events while also stretching the boundaries of what we know to be true. The resulting fake news becomes difficult to counter because it goes beyond questions of fact and enters the realm of interpretation, enabled by widespread, networked belief.