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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. 

Substance use disorders (SUDs) are characterized by an inability to decrease a substance use (e.g., alcohol or opioids) despite negative repercussions. SUDs are clinically diagnosable, hazardous, and considered a public health issue. Sponsorship, a specialized type of peer mentorship, is vital in the recovery process and originates from 12-step fellowship programs such as Alcoholics Anonymous (AA) and Narcotics Anonymous (NA). To investigate sponsorship relationship practices and to identify design opportunities for digitally-mediated peer support, we conducted 27 in-depth interviews with members of AA and NA. We identified five key sponsorship relationship practices relevant for designing social computing tools to support sponsorship and recovery: 1) assessing dyadic compatibility, 2) managing sponsorship with or without technology, 3) establishing boundaries, 4) building a peer support network, and 5) managing anonymity. We identify social computing and digitally-mediated design opportunities and implications.