User agency–based versus machine agency–based misinformation interventions: The effects of commenting and AI fact-checking labeling on attitudes toward the COVID-19 vaccination

Author:

Lee Jiyoung1ORCID,Bissell Kim2

Affiliation:

1. Sungkyunkwan University, Republic of Korea

2. The University of Alabama, USA

Abstract

This study aimed to examine the effects of commenting on a Facebook misinformation post by comparing a user agency–based intervention and machine agency–based intervention in the form of artificial intelligence (AI) fact-checking labeling on attitudes toward the COVID-19 vaccination. We found that both interventions were effective at promoting positive attitudes toward vaccination compared to the misinformation-only condition. However, the intervention effects manifested differently depending on participants’ residential locations, such that the commenting intervention emerged as a promising tool for suburban participants. The effectiveness of the AI fact-checking labeling intervention was pronounced for urban populations. Neither of the fact-checking interventions showed salient effects with the rural population. These findings suggest that although user agency- and machine agency–based interventions might have potential against misinformation, these interventions should be developed in a more sophisticated way to address the unequal effects among populations in different geographic locations.

Funder

Ministry of Education of the Republic of Korea and the National Research Foundation of Korea

Natural Hazards Center, University of Colorado Boulder

Publisher

SAGE Publications

Subject

Sociology and Political Science,Communication

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