Guardrail Selection in Line Charts to Contextualize Persuasive Visualizations

2026-05-18

AI Summary

This study addresses the prevalence of misinterpretation in line charts on social media and interactive platforms, often exacerbated by selective data presentation and misleading titles. It introduces and empirically evaluates a novel set of “guardrail” sampling strategies—contextual reference lines embedded within visualizations to enrich data context. Through a pre-registered mixed-methods experimental design using real-world datasets (including COVID-19 and stock market data), user studies demonstrate that these guardrails significantly improve viewers’ trust in the chart, accuracy of their judgments, and perception of contextual completeness compared to baseline charts without such aids. The research also uncovers nuanced user preferences across different guardrail types, offering deployable, practical solutions for enhancing trustworthy data visualization.

Abstract

Charts used for persuasion can easily veer into being outright misleading when, for instance, cherry-picked data is paired with a deceptive caption, as is commonly encountered on social media. The rise of interactive time-series data explorers for hotly debated topics makes such framing easy to produce and spread. Post-hoc interventions like fact-checking often arrive too late and suffer from persistence of belief. Prior work suggests that guardrails, in the form of contextual comparison lines embedded directly into charts, can reduce these effects. We propose and evaluate a practical set of guardrail sampling strategies for implementing such contextual lines in real systems. In a preregistered mixed-design study with two real-world scenarios (COVID-19 and Stocks), participants viewed persuasive charts with different sets of guardrails and reported trust, estimated rank in the dataset, expressed their perceived completeness of context, as well as subjective preference for different tasks. Across scenarios, guardrails improved trust, accuracy of performance judgments, and perceived completeness of context compared to the control. Taken together, the study offers practical guardrail sampling methods, evidence of their contextual benefits, and insights into participants' preferences.

Problem

• persuasive visualizations
• misleading charts
• guardrails
• contextual comparison
• time-series data

Innovation

• guardrail sampling
• contextual visualization
• persuasive charts
• line charts
• misleading visualization