Prediction market visualizations, betting, and uncertainty: A study of Reddit Posts and Comments

Authors

Subham Sah (University of North Carolina at Charlotte), Alireza Karduni (Simon Fraser University), Doug Markant (University of North Carolina at Charlotte), Wenwen Dou (UNC Charlotte)

Keywords

Data Visualization, Prediction Market, Uncertainty Visualization, Human Computer Interaction

Abstract

Prediction market platforms present contracts about future events through visualizations that show probabilities, prices, trends, odds, and payout information. Although these visualizations often appear precise, they do not always show uncertainty directly. As a result, users infer uncertainty from market movement, visualization cues, and contextual information. In this paper, we examine how users interpret prediction market visualizations through a qualitative analysis of posts and comments from the Reddit community r/Kalshi. From an initial corpus of approximately 12,000 posts and 96,000 comments, we identified 360 posts containing prediction market visualizations and conducted a thematic analysis of annotated posts and related discussions. Our findings show that users infer uncertainty through several forms of interpretation: they interpret chart values, struggle with probability information displayed, bring in external knowledge, question credibility and liquidity, critique visualization design, and connect visualized information to betting decisions.