Erika Oh
Dr. Oh specializes in artificial intelligence (AI) dialogue systems, commonly referred to as AI chatbots.
Publications
Journal Articles
When distrust shapes news choice: Perceptions of mis-and disinformation and news consumption across traditional and social media outlets
Published in Cyberpsychology, Behavior, and Social Networking, 2026
While trust in the news media has eroded globally, this shift is particularly noticeable in the United States. This lack of trust has been attributed to perceptions that the news media is either unintentionally (misinformation) or intentionally (disinformation) spreading false information. This study examined the relationship between perceptions of misinformation (PMI) and disinformation (PDI) and traditional and social media news use. A survey of US adults (N = 1005) revealed that both PMI and PDI were negatively associated with television and newspaper news use. Furthermore, PMI was positively associated with YouTube, TikTok, and Instagram news use, whereas PDI was positively associated with YouTube and TikTok news use. Our findings highlight the roles PMI and PDI play in the selection of specific outlets for news consumption and offer implications in understanding how individuals engage in news selection, which could expose them to mis- and disinformation.
Recommended citation: Rasul, M. E., Oh, Y. J., Moonsun, J., Cho, H. J., & Calabrese, C. (2026). When Distrust Shapes News Choice: Perceptions of Mis- and Disinformation and News Consumption Across Traditional and Social Media Outlets. Cyberpsychology, Behavior, and Social Networking, 29(3), 151-158. https://doi.org/10.1177/21522715261424695
Leveraging artificial intelligence chatbots to employ bypassing and correction strategies for addressing misinformation about contraceptive use
Published in Science Communication, 2026
We examined whether bypassing and combined (correction with bypassing) strategies delivered through artificial intelligence (AI) chatbots can address contraceptive misinformation. In Study 1, we found through observational reddit data that bypassing, correction, and combined strategies were present in online discussions and were more engaging than other responses. In Study 2, an experiment employing AI chatbots found that the combined strategy improved recommendation intentions compared with the control conditions, while also reducing beliefs in misinformation. The combined strategy AI chatbot was viewed as warmer and more competent than the correction, invoking less reactance and increasing recommendation intentions. Practical and theoretical implications are discussed.
Recommended citation: Calabrese, C., Xue, H., Zhang, X., & Oh, Y. J. (2026). Leveraging Artificial Intelligence Chatbots to Employ Bypassing and Correction Strategies for Addressing Misinformation About Contraceptive Use. Science Communication. https://doi.org/10.1177/10755470261418533
Targeting anger for COVID-19 prevention: The motivating role of anger on media use and vaccination intention
Published in PLOS One, 2025
The COVID-19 pandemic resulted in public anger due to its disruptive and harmful nature. However, anger remains an understudied concept despite its potential to persuade the public and spark action. The current study investigates the role of anger in driving COVID-19 vaccination intentions. In Study 1, through a rolling-cross sectional survey of U.S. adults during the early stages of the COVID-19 epidemic (N = 6,141), it was found that anger towards COVID-19 was associated with increased use of social and traditional media news, which was then related to improved vaccination intentions. In Study 2, utilizing computational analysis of a Twitter (now X) dataset using an AI classifier, 15 targets of anger were identified from real-world anger expressions in social media discourse about COVID-19. Building on these insights, Study 3 involved a representative survey of U.S. adults during the post-emergency declaration stage of COVID-19 (N = 1,005). This survey aimed to replicate the findings of Study 1 while incorporating the anger targets identified in Study 2. The results revealed that different targets of anger were associated with vaccination intentions through the consumption of traditional news media. Although social media was a prominent channel for news about vaccination at the beginning of the pandemic, our findings suggest that traditional media news use may be an important link in understanding the relationship between anger and vaccination intentions. Theoretical, practical, and methodological implications are discussed.
Recommended citation: Oh, Y. J., Rasul, M. E., Lim, J. I., Calabrese, C., McKinley, E., Stevens, H., Turner, M. M., Lapinski, M. K., & Peng, T. Q. (2025). Targeting anger for COVID-19 prevention: The motivating role of anger on media use and vaccination intention. PLOS One, 20(12), e0338183.https://doi.org/10.1371/journal.pone.0338183