Election predictions in the news: how users perceive and respond to visual election forecasts

Abstract

ABSTRACT Political journalism often tries to predict the future, especially the outcomes of elections. This has historically been accomplished through written articles or opinion pieces. A more recent development involves the publication of data-driven predictions in online news media. These news items not only contain an estimate for the election results but also often try to visualize potential uncertainties of the prediction. However, the ways in which users react to these forms of journalism have not yet been studied extensively. In this work, we survey users of a predictive journalism piece on the 2021 German federal elections published by the German newspaper Süddeutsche Zeitung to better understand their reactions. While we found an alignment between the designers' intention to show the inherent uncertainty of election predictions with the audience's reception, we encountered mixed results in users' ability to interpret the uncertainty visualizations presented. Most respondents indicated that the predictions did not influence their thinking about the race, and some remained skeptical toward such predictions published by journalists for various reasons. Based on these findings, we suggest the need for rigorous user testing of visualizations for election prediction and increased awareness and future research on ways to increase the transparency of methods and data to develop appropriate trust toward predictive journalism.