Follow Nudges without Budges: A Field Experiment on Misinformation Followers Didn't Change Follow Networks

2025-12-15

AI Summary

Digital health misinformation undermines public health, yet scalable interventions to redirect affected users toward authoritative sources remain understudied. Method: We conducted a randomized controlled field experiment on X (N = 28,582), introducing and empirically testing the “follow nudge”—a novel digital advertising intervention—comparing four source-message combinations: neutral vs. value-driven messaging crossed with institutional (e.g., WHO) vs. influencer sources. Contribution/Results: The value-driven message paired with a reputable health institution significantly increased follow-through rates (p < 0.001, Bonferroni-corrected), confirming the synergistic effect of source credibility and persuasive framing. However, overall click-through rates were low and cost-per-acquisition high, indicating limited cost-effectiveness under current ad mechanisms. This study provides actionable, lightweight behavioral evidence for platform-based countermisinformation governance and extends both the theoretical scope and empirical foundation of digital nudging in health communication.

Technology Category

• Application Domains: Misinformation & Fake News
• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Humans and AI: Learning Human Values and Preferences

Application Category

• Responsible Web: Mitigating misinformation and disinformation
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Can digital ads encourage users exposed to inaccurate information sources to follow accurate ones? We conduct a large-scale field experiment (N=28,582) on X, formerly Twitter, with users who follow accounts that spread health misinformation. Participants were exposed to four ad treatments varied on two dimensions: a neutral message versus a persuasive message appealing to values of independence, and a request to follow a health institution versus a request to follow a health influencer. We term this ad-based, social network intervention a follow nudge. The ad with a persuasive message to follow a well-known health institution generated significantly higher click-through rates than all other conditions (Bonferroni-corrected pairwise tests, all p<0.001). Given the overall low click-through rate across treatments and the high cost of digital advertising infrastructure on X, however, we conclude that our proposed intervention -- at least in its current ad-based format -- is not a cost-effective means to improve information environments online. We discuss challenges faced when conducting large-scale experiments on X following the platform's ownership change and subsequent restrictions on data access for research purposes.

Problem

• Test if digital ads shift misinformation followers to accurate sources
• Evaluate ad effectiveness in changing social media follow networks
• Assess cost-effectiveness of ad-based interventions for online information quality

Innovation

• Persuasive ads target misinformation followers
• Test neutral vs value-based messaging strategies
• Evaluate follow nudges for network intervention