A holistic framework for the analysis of predictive rhetoric in digital visualizations

Abstract

In digital culture, visualizations are a prevalent and ubiquitous form of communication. A veteran journalistic tool, and an increasingly popular one in digital politics, visualizations offer informative value, attract readership, and increase engagement. Visualizations’ multimodality enables them to convey rhetoric through informative, narrative and visual strategies, making them particularly well-suited for future-oriented discourse. Despite the rise of visualization-focused scholarly work over the past decade, several analytical lacunas remain, due to visualizations’ multimodal nature and their rich array of actors, contexts and usages in the digital world. Specifically, no scholarly approach examines forward-looking visualizations comprehensively, addressing the ways in which their rhetorical layers coalesce to broker knowledge in multimodal predictive discourse. To fill this gap, our paper proposes a holistic framework for their analysis, addressing knowledge-brokering functions, predictive components, and rhetorical strategies. Thus, we ask, ‘How are predictive visualizations rhetorically constructed to mediate the future?’ and answer through conceptualization complemented by qualitative analysis of predictive pandemic visualizations from journalistic and social media. We begin by creating a theoretically informed framework, based on existing perspectives from data-journalism studies, projection studies, and visualization scholarship, which we then refine through analytical workshops and empirical application. Our final analytical framework encapsulates each visualization’s rhetorical strategies, its knowledge-brokering functions, predictive structure, and their interrelations, highlighting the division of rhetorical and predictive labor across each visualization’s components. We conclude with an analytical epilogue in which we demonstrate the usefulness of this framework in holistically analyzing predictive multimodal rhetoric by revisiting the elusive concept of rhetorical complexity in predictive visualizations.