The Digital Gatekeeper: How Personalization Algorithms and Mobile Applications Have Changed News Forever

Abstract

In the age of big data and the personalized web, news too has become personalized. Headlines seem to magically align with our unique tastes, stories echo previously searched items, and recommender systems tease our eyes with topics we “might like to read.” A new age of “editorialism,” methods of news personalization are part computer science, and part art. Today, not only do journalists determine what news we read, but also software developers and computational algorithms that monitor our behavior. Because news gives people information to act in society, the power of this new editorial system and its unlimited variations should cause for pause. For example, only computer algorithms aggregate some mobile application newsfeeds, whereas a balance of humans and computers drive others. This thesis seeks to unpack why differences in mobile news application outputs matter and how these platform variations affect users. Important questions that will be answered include: (1) Do mobile news app users feel like news personalization gives them news they would like to read? and (2) Do people generally understand how personalization algorithms work? Currently, news personalization is lauded as a seamless phenomenon where people get the information they want. But what people want, is not always what they need.