Economics and Finance Faculty Publications and Presentations
Document Type
Article
Publication Date
8-24-2025
Abstract
Although government agencies and fact-checking organizations issue correction messages to mitigate misinformation dissemination on social media, their efforts have been largely ineffective. Drawing on Information Manipulation Theory (IMT) and information extracted from over 84 million tweets, we examine the impact of correction messages and explore how different information updates affect their effectiveness. Our empirical approach differentiates between subpopulations of correction messages. The results support the existence of two distinct types: correction messages that significantly mitigate the spread of fake news—a 1 percent increase in “effective” messages decreases the spread of fake news by 0.89 percent; and those that amplify the misinformation—a 1 percent increase in “ineffective” messages increases the spread of fake news by 1.37 percent. Despite the higher count of “effective” correction messages, they are less potent than their “ineffective” counterparts. Our study extends the tenets of IMT to correction messages to identify effective platform interventions and highlight the efficacy of information updates in reducing the spread of fake news. Furthermore, it offers significant insights to social media platforms and fact-checking organizations on designing and deploying effective corrections.
Recommended Citation
King, K.K. and Escobari, D., 2025. Can Correction Messages Reduce the Spread of Fake News on Social Media? The Impact of Information Updates on the Effectiveness of Corrections. Journal of Management Information Systems, 42(3), pp.706-736. https://doi.org/10.1080/07421222.2025.2520174
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Title
Journal of Management Information Systems
DOI
10.1080/07421222.2025.2520174
Comments
© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.