TMI: INFORMATION RHETORIC TYPES IN DIGITAL POLITICAL INFOGRAPHICS

  • Eedan Amit-Danhi Hebrew University, Israel
Keywords: Information, Data Visualization, election, rhetoric, visual rhetoric

Abstract

Visualizations are reliant on visual encoding, in which attributes of data are depicted through graphic symbols (Cairo, 2019). As such, they are placed as a transitional mode between data and information in the linear framework of the "wisdom hierarchy" (DIKW). In the digital information environment, both the linear learning process and the distinction between data and information merit a re-evaluation. This paper seeks to create a better understanding of information's role in digital culture, by venturing to re-examine its attributes. Relying on a sample of all visualizations posted by the top four candidates of the 2016 US elections (n=252), I applied qualitative grounded analysis informed by theory: First, I constructed a conceptual model for the attributes of information, which relies on three layers – (1) foundation (substantiation/sources); (2) building blocks (data components); (3) data-structures (analysis). Second, following a classification of all units according to this model, I defined types of visualization rhetoric that each rely on specific formulations of information attributes (foundation, building blocks and structure) to make a political argument. Finally, I identify two modes of visual information-rhetoric in elections: unveiling and imagining. The model and categories defined in this study demonstrate how the rhetorical agility required for modern political campaigning seems to muddle the axiomatic distinctions of data and information and create new, unpredictable hybrid information and rhetorical types, some of which rely heavily on estimations and fantasy, rather than empirical observation and evidence.

Published
2020-10-05
How to Cite
Amit-Danhi, E. (2020). TMI: INFORMATION RHETORIC TYPES IN DIGITAL POLITICAL INFOGRAPHICS. AoIR Selected Papers of Internet Research, 2020. https://doi.org/10.5210/spir.v2020i0.11156
Section
Papers A