Augmenting Web Pages and Search Results to Support Credibility Assessment
ACM Conference on Computer-Human Interaction |
The presence (and, sometimes, prominence) of incorrect and misleading content on the Web can have serious consequences for people who increasingly rely on the internet as their information source for topics such as health, politics, and financial advice. In this paper, we identify and collect several page features (such as popularity among specialized user groups) that are currently difficult or impossible for end-users to assess, yet provide valuable signals regarding credibility. We then present visualizations designed to augment search results and Web pages with the most promising of these features. Our lab evaluation finds that our augmented search results are particularly effective at increasing the accuracy of users’ credibility assessments, highlighting the potential of data aggregation and simple interventions to help people make more informed decisions as they search for information online.
You can also download the associated data set.