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

Laura Kurek, Joshua Ashkinaze, Ceren Budak, Eric Gilbert

TL;DR

This study tests whether targeted ads can encourage followers of health misinformation spreaders to adopt high-quality information sources. Using a large field experiment on X with 28,582 participants and four ad conditions, the authors find that a persuasive message promoting a health institution yields the highest click-through rate, but overall engagement and actual follows remain extremely low, raising questions about cost-effectiveness. The research highlights substantial platform-data access challenges after X's ownership change, which prevented direct measurement of follows and forced reliance on proxies. The findings suggest misinformation networks are resistant to ad-based network nudges, and underline the need for alternative strategies and improved data access for scalable misinformation interventions.

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.

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

TL;DR

This study tests whether targeted ads can encourage followers of health misinformation spreaders to adopt high-quality information sources. Using a large field experiment on X with 28,582 participants and four ad conditions, the authors find that a persuasive message promoting a health institution yields the highest click-through rate, but overall engagement and actual follows remain extremely low, raising questions about cost-effectiveness. The research highlights substantial platform-data access challenges after X's ownership change, which prevented direct measurement of follows and forced reliance on proxies. The findings suggest misinformation networks are resistant to ad-based network nudges, and underline the need for alternative strategies and improved data access for scalable misinformation interventions.

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.

Paper Structure

This paper contains 32 sections, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Individual-level interventions
  4. Environment-level interventions
  5. Experiment Design
  6. Participants
  7. Identifying health misinformation stories
  8. Identify whether spreaders of the health misinformation stories have X (Twitter) accounts
  9. Identify prolific health misinformation spreaders with large followings
  10. Identify followers of spreaders of health misinformation stories on X (Twitter)
  11. Stimuli
  12. Factor 1: Message Type
  13. Factor 2: Account to Follow
  14. Procedure
  15. Findings
  16. ...and 17 more sections

Figures (4)

  • Figure 1: The follow nudge intervention intends to add high-quality information ties within low-quality information networks.
  • Figure 2: The four ad treatments, varied along two dimensions: (1) a neutral versus a persuasive message and (2) a request to follow a U.S. health institution versus a request to follow a health influencer
  • Figure 3: Comparison of click-through rates across ad treatments with standard error bars
  • Figure 4: Survey results for two subsets of participants. On the left, a heatmap of responses from those who did not click the ad. On the right, a heatmap of responses from those who clicked the ad, but chose not to follow the promoted account.