CommSense: Facilitating Bias-Aware and Reflective Navigation of Online Comments for Rational Judgment

2026-01-27

AI Summary

This study addresses how algorithmic presentation of online reviews can induce cognitive biases such as anchoring, noting that prior research has largely overlooked the dynamic evolution of users’ judgment processes. To bridge this gap, the authors model review interaction as a four-stage workflow and employ a mixed-methods approach—including a user study (N=18), co-design workshops, and a controlled experiment (N=24)—to identify core user needs at each stage. They propose an integrated interface strategy combining pre-exposure guidance, interactive organization, reflective prompts, and holistic support, implemented in a browser extension called CommSense. Findings demonstrate that CommSense, through lightweight visual overviews and subtle cues, significantly enhances users’ awareness of bias and capacity for reflection, leading to more comprehensive, evidence-based judgments while maintaining high usability.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Machine Learning: Learning Preferences or Rankings

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Online comments significantly influence users'judgments, yet their presentation, often determined by platform algorithms, can introduce biases, such as anchoring effects, which distort reasoning. While existing research emphasizes mitigating individual cognitive biases, the evolution of user judgments during comment engagement remains overlooked. This study investigates how presentation cues impact reasoning and explores interface design strategies to mitigate bias. Through a preliminary experiment (N=18) and a co-design workshop, we identified key challenges users face across a four-stage process and distilled four design requirements: pre-engagement framing, interactive organization, reflective prompts, and synthesis support. Based on these insights, we developed CommSense, an on-the-fly plugin that enhances user engagement with online comments by providing visual overviews and lightweight prompts to guide reasoning. A between-subject evaluation (N=24) demonstrates that CommSense improves bias awareness and reflective thinking, helping users produce more comprehensive, evidence-based rationales while maintaining high usability.

Problem

• online comments
• cognitive bias
• anchoring effect
• rational judgment
• bias-awareness

Innovation

• bias-aware interface
• reflective prompting
• online comment navigation
• anchoring effect mitigation
• on-the-fly plugin