ABSTRACT
Misinformation presented in different modalities about the COVID-19 pandemic has been prevalent. One approach to reducing the negative effects of misinformation is through corrective information. However, it is possible that people develop counter-attitude towards the corrective information and reaffirm their belief in misinformation, called the boomerang effect. Fewer studies examined how different modes of corrective information about COVID-19 may address the boomerang effect. With a 3-by-3 between-subject experiment design (n = 210), we first presented one of the three modalities of misinformation (text, image, video) to the participants, followed by one of the three modalities of corrective information (text, image, video) to examine the effect of the corrective information. The results showed that there was no boomerang effect after correction in all modalities, indicating that all corrective information successfully reduced participants' perceived credibility and potential action for misinformation. In the post-hoc analysis, the correction in the video mode worked best on text misinformation. Our results also suggested that image misinformation worked least effectively in terms of conveying misinformation. © 2022 Owner/Author.
ABSTRACT
We conducted a lab-based eye-Tracking study to investigate how interactivity of an AI-powered fact-checking system affects user interactions, such as dwell time, attention, and mental resources involved in using the system. A within-subject experiment was conducted, where participants used an interactive and a non-interactive version of a mock AI fact-checking system, and rated their perceived correctness of COVID-19 related claims. We collected web-page interactions, eye-Tracking data, and mental workload using NASA-TLX. We found that the presence of the affordance of interactively manipulating the AI system's prediction parameters affected users' dwell times, and eye-fixations on AOIs, but not mental workload. In the interactive system, participants spent the most time evaluating claims' correctness, followed by reading news. This promising result shows a positive role of interactivity in a mixed-initiative AI-powered system. © 2022 ACM.