Data journalism’s many futures: Diagrammatic displays and prospective probabilities in data-driven news predictions

Abstract

This article explores how newsmakers exploit numeric records in order to anticipate the future. As this nascent area of data journalism experiments with predictive analytics, we examine its reports and computer-generated presentations, often infographics and data visualizations, and ask what time frames and topics are covered by these diagrammatic displays. We also interrogate the strategies that are employed in order to modulate the uncertainty involved in calculating for more than one possible outlook. Based on a comprehensive sample of projects, our analysis shows how data journalism seeks accuracy but has to cope with a number of different prospective probabilities and the puzzle of how to address this multiplicity of futures. Despite their predictive ambition, these forecasts are inherently grounded in the past because they are based on archival data. We conclude that this form of quantified premediation limits the range of imaginable future thoughts to one preferred mode, namely extrapolation.