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Title: Pushing the (Visual) Narrative: the Effects of Prior Knowledge Elicitation in Provocative Topics
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.  more » « less
Award ID(s):
1755611
NSF-PAR ID:
10133071
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
CHI'20: ACM Conference on Human Factors in Computing Systems
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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    Significance Statement

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