Pop: Bursting News Filter Bubbles on Twitter Through Diverse Exposure

An increasing number of American adults are consuming news on social media platforms. However, these digital platforms employ personalized recommendation algorithms to increase user engagement. This selective exposure to information leads to the formation of filter bubbles where the users are constantly fed information in line with their ideological views. In this paper, we aim at bursting these filter bubbles through diverse exposure. We discuss the design of a Google Chrome extension, Pop, which augments user's Twitter feeds with news tweets from agencies of different ideological standings.