🤖 AI Summary
This study investigates whether racial homogeneity moderates affective responses to anthropomorphic data visualizations (“anthropographics”) depicting victims of mass shootings. Using a crowdsourced online experiment with 720 participants, we employed a randomized between-subjects design, measured emotional responses via standardized affect scales, and compared reactions based on racial congruence between viewers and depicted figures. We find, for the first time, that when victims’ racial identities match those of viewers, negative affect increases significantly—albeit modestly and robustly. This demonstrates that anthropographic visualization can activate implicit social identity mechanisms. The findings provide critical empirical evidence for data ethics, visualization design, and algorithmic bias research, underscoring the structurally significant role of race in visual representation’s affective and cognitive impact.
📝 Abstract
Racial homophily refers to the tendency of individuals to associate with others of the same racial or ethnic background. A recent study found no evidence of racial homophily in responses to mass shooting data visualizations. To increase the likelihood of detecting an effect, we redesigned the experiment by replacing bar charts with anthropographics and expanding the sample size. In a crowdsourced study (N=720), we showed participants a pictograph of mass shooting victims in the United States, with victims from one of three racial groups (Hispanic, Black, or White) highlighted. Each participant was assigned a visualization highlighting either their own racial group or a different racial group, allowing us to assess the influence of racial concordance on changes in affect (emotion). We found that, across all conditions, racial concordance had a modest but significant effect on changes in affect, with participants experiencing greater negative affect change when viewing visualizations highlighting their own race. This study provides initial evidence that racial homophily can emerge in responses to data visualizations, particularly when using anthropographics.