Abstract

Police departments use public dashboards to share use-of-force data for policymaking and public awareness, but it remains unclear how visualization formats affect how people interpret this information. This between-subjects study with 64 participants compares absolute use-of-force incident counts (Totals) and population-adjusted rates (Rates) across four United States cities. The research included a quantitative analysis of graph comprehension, policy prioritization, confidence ratings, and attitude change, as well as a qualitative examination of open-ended responses. Results showed a strong framing effect: those who viewed absolute numbers prioritized Aurora, Colorado (highest incidents) for policy intervention, often disregarding population baselines, while those viewing per-capita rates prioritized Burlington, Vermont (highest rate). Despite high visual literacy, participants made confident policy recommendations while admitting insufficient data. Both groups requested race-specific incident breakdowns, which were missing. Findings suggest effective police transparency requires integrated presentations of absolute numbers, per-capita rates, and race-specific data to support valid policy decisions.

Publication Date

4-2026

Document Type

Master's Project

Student Type

Graduate

Degree Name

Human-Computer Interaction (MS)

Department, Program, or Center

Information, School of

College

Golisano College of Computing and Information Sciences

Advisor

Hidy Kong

Advisor/Committee Member

Ji Hwan Park

Campus

RIT – Main Campus

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