Prior Elicitation in Narrative Visualization

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Description: Narrative visualization is a popular style of data-driven storytelling. Authors use this medium to engage viewers with complex and sometimes controversial issues. A challenge for authors is to not only deliver new information, but to also overcome people's biases and misconceptions. We study how people adjust their attitudes toward (or away from) a message experienced through a narrative visualization. In a mixed-methods analysis, we investigate whether eliciting participants' prior beliefs, and visualizing those beliefs alongside actual data, can increase narrative persuasiveness. We find that incorporating priors does not significantly affect attitudinal change. However, participants who externalized their beliefs expressed greater surprise at the data. Their comments also indicated a greater likelihood of acquiring new information, despite the minimal change in attitude. Our results also extend prior findings, showing that visualizations are more persuasive than equivalent textual data representations for exposing contentious issues. We discuss the implications and outline future research directions.

License: GNU General Public License (GPL) 3.0

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