[Paper Review] Social Media COVID-19 Misinformation Interventions Viewed Positively, But Have Limited Impact

Christine Geeng, Tiona Francisco+2 more|arXiv (Cornell University)|Dec 21, 2020

Misinformation and Its Impacts13 references13 citations

TL;DR

This study evaluates user attitudes and effectiveness of social media interventions for COVID-19 misinformation on Facebook, Twitter, and Instagram in late March 2020. While users viewed post-specific 'false information' labels positively and found them more helpful than generic banners, 76.7% corrected misinformation through web searches or trusted health sites, indicating platforms are not yet the primary source of correction despite user receptiveness to interventions.

ABSTRACT

Amidst COVID-19 misinformation spreading, social media platforms like Facebook and Twitter rolled out design interventions, including banners linking to authoritative resources and more specific "false information" labels. In late March 2020, shortly after these interventions began to appear, we conducted an exploratory mixed-methods survey (N = 311) to learn: what are social media users' attitudes towards these interventions, and to what extent do they self-report effectiveness? We found that most participants indicated a positive attitude towards interventions, particularly post-specific labels for misinformation. Still, the majority of participants discovered or corrected misinformation through other means, most commonly web searches, suggesting room for platforms to do more to stem the spread of COVID-19 misinformation.

Motivation & Objective

• To understand public attitudes toward social media platform interventions for COVID-19 misinformation.
• To assess the perceived effectiveness of generic banners versus post-specific 'false information' labels.
• To identify the primary sources through which users discovered misinformation was false.
• To explore the role of social media interventions in correcting misinformation compared to other user-driven strategies.
• To inform future platform design and policy by identifying gaps in current intervention effectiveness.

Proposed method

• Conducted a mixed-methods online survey with 311 participants recruited via Prolific and personal networks.
• Used anonymous, self-reported data collected between March 20–26, 2020, during early rollout of interventions.
• Collected both quantitative ratings of intervention helpfulness and qualitative accounts of how users learned misinformation was false.
• Analyzed responses to compare effectiveness of generic banners versus post-specific labels.
• Screened participants to ensure they had used Facebook, Twitter, or Instagram since March 1, 2020, to ensure exposure to interventions.
• Used IRB-exempt methodology with no identifying data collected, and anonymized quotes with participant consent.

Experimental results

Research questions

• RQ1 What are people’s attitudes toward social media platform interventions for COVID-19 misinformation, including generic banners and post-specific false information labels?
• RQ2 How did participants discover that COVID-19 misinformation they had seen was false, and what role did platform interventions play in this discovery?
• RQ3 To what extent do users self-report that platform interventions corrected their misinformation beliefs compared to other methods?
• RQ4 How do user demographics and trust in platforms influence responses to misinformation interventions?
• RQ5 What are the potential side effects or unintended consequences of platform-based misinformation interventions?

Key findings

• Participants rated Facebook’s post-specific 'False Information' label significantly more helpful than its generic COVID-19 information banner.
• 76.7% of participants discovered misinformation was false through web searches or trusted health websites, not through platform interventions.
• Despite positive attitudes, only 35.3% of participants corrected others who shared misinformation, and 27.18% corrected themselves after initially believing it.
• Post-specific labels were perceived as more effective than generic banners, suggesting targeted labeling may improve intervention impact.
• A minority of users expressed distrust in platform interventions, indicating potential resistance among some user groups.
• The study highlights a gap between user receptiveness to interventions and their actual role in correcting misinformation, with users relying more on external sources.