CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking

TL;DR

This paper introduces CobWeb, a prototype interface that visualizes user bias in political fact-checking to improve user awareness and decision-making, highlighting the importance of perceived source reputation.

Contribution

It presents a novel user interface for estimating and visualizing user bias in political fact-checking, addressing a gap in user-experience research.

Findings

80% of users found bias indicators useful

User bias estimation based on perceived source reputation

Enhanced user awareness in political fact-checking

Abstract

The effect of user bias in fact-checking has not been explored extensively from a user-experience perspective. We estimate the user bias as a function of the user's perceived reputation of the news sources (e.g., a user with liberal beliefs may tend to trust liberal sources). We build an interface to communicate the role of estimated user bias in the context of a fact-checking task. We also explore the utility of helping users visualize their detected level of bias. 80% of the users of our system find that the presence of an indicator for user bias is useful in judging the veracity of a political claim.