The Nudging Effect of Accuracy Alerts for Combating the Diffusion of Misinformation: Algorithmic News Sources, Trust in Algorithms, and Users’ Discernment of Fake News

ABSTRACTResearch has revealed that the diffusion of misinformation online can be attributed to inaccuracies in human cognitive reasoning. We examine the nudging effect of Accuracy Alerts on users' ability to discern misinformation and how their trust moderates this effect. The results from a 2 (accuracy nudge: with nudge vs. no nudge) × 2 (news source type: algorithmic news vs. legacy non-algorithmic news) experiment showed significant main and interaction effects indicating that an algorithmic source effect is present in the process of nudge acceptance. Misinformation sharing intention was largely lower for legacy non-algorithmic news than algorithmic news, but there was a greater decrease in algorithmic news when nudging was employed. Disclosure statementNo potential conflict of interest was reported by the author(s).Supplemental DataSupplemental data for this article can be accessed online at https://doi.org/10.1080/08838151.2023.2175830Additional informationNotes on contributorsDonghee ShinDonghee Shin (Ph.D. & M.A., Syracuse University) is a professor at the College of Communication and Media Sciences at Zayed University. His research interests include digital journalism, human-computer interaction, and algorithmic media. His recent research in computer/algorithm as media addresses: embodied cognition, the subjective value of information, interaction, and interactivity.Kerk F. KeeKerk F. Kee (Ph.D., the University of Texas at Austin) is an associate professor at the College of Media & Communication at Texas Tech University. His research primarily investigates the development, adoption, implementation, and ultimate diffusion of big data technologies in scientific organizations. He also studies the dissemination of health information in cultural communities and the spread of pro-environmental attitudes in modern societies.Emily Y. ShinEmily Y. Shin is a researcher at the Human-Computer Interaction Lab at Zayed University, Dubai, United Arab Emirates. Her research interests are in the areas of emerging information technologies and their impact on usability, interface, and user experience. She has participated in numerous interdisciplinary projects on human-AI research.