The Algorithmic Amplification of Concerns in a Media-Saturated World

We are living in an age of information abundance amplified by the science of recommendation engines––algorithmically selected content based on personal data profiles dominates the modern media landscape. The intersection of information abundance, human psychology, and user data profiling in modern society is at the heart of media recommendation algorithms. Our lives have come online. We are exposed to media consumption; we live in and through media. The function of the algorithmic media (media platforms such as Facebook, YouTube, Twitter, Netflix, Amazon, etc. are driven by algorithmic operation) is to facilitate mediated interaction, provide information, and give search results to users depending on their algorithmic operations. Algorithmic media platforms act as “performative intermediaries” (Bucher 1) in shaping opinions and altering the course of history. The current paper explores the algorithmic basis of social media and other content search or recommendation systems where our encounters with algorithms constitute a key site of many things––power, politics, propaganda, governance, and governmentality. The aim of the paper is to understand what these encounters generate.