Visualization Vibes: The Socio-Indexical Function of Visualization Design
Michelle Morgenstern, Amy Rae Fox, Graham M. Jones, Arvind Satyanarayan
Abstract
In contemporary information ecologies saturated with misinformation, disinformation, and a distrust of science itself, public data communication faces significant hurdles. Although visualization research has broadened criteria for effective design, governing paradigms privilege the accurate and efficient transmission of data. Drawing on theory from linguistic anthropology, we argue that such approaches-focused on encoding and decoding propositional content-cannot fully account for how people engage with visualizations and why particular visualizations might invite adversarial or receptive responses. In this paper, we present evidence that data visualizations communicate not only semantic, propositional meaning-meaning about data-but also social, indexical meaning-meaning beyond data. From a series of ethnographically-informed interviews, we document how readers make rich and varied assessments of a visualization's "vibes"-inferences about the social provenance of a visualization based on its design features. Furthermore, these social attributions have the power to influence reception, as readers' decisions about how to engage with a visualization concern not only content, or even aesthetic appeal, but also their sense of alignment or disalignment with the entities they imagine to be involved in its production and circulation. We argue these inferences hinge on a function of human sign systems that has thus far been little studied in data visualization: socio-indexicality, whereby the formal features (rather than the content) of communication evoke social contexts, identities, and characteristics. Demonstrating the presence and significance of this socio-indexical function in visualization, this paper offers both a conceptual foundation and practical intervention for troubleshooting breakdowns in public data communication.
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Install the CLIlune papers fulltext 43bee430-b2a1-47d6-b6a1-df068523b363Cited by top-tier papers2
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