CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking
This addresses user bias in fact-checking for political contexts, but it is incremental as it builds on existing bias estimation methods.
The paper tackled the problem of user bias in political fact-checking by estimating bias based on perceived news source reputation and building an interface to communicate it, finding that 80% of users found the bias indicator useful for judging claim veracity.
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.