Evidence-Based Misinformation Interventions: Challenges and Opportunities for Measurement and Collaboration

• Published in: Policy File 2023
• Main Authors: Green, Yasmin, Gully, Andrew, Roth, Yoel, Roy, Abhishek, Tucker, Joshua A, Wanless, Alicia
• Format: Report
• Language: English
• Subjects: Big Data; Carnegie Endowment for International Peace - US

The lingering coronavirus pandemic has only underscored the need to find effective interventions to help internet users evaluate the credibility of the information before them. Yet a divide remains between researchers within digital platforms and those in academia and other research professions who are analyzing interventions. Beyond issues related to data access, a challenge deserving papers of its own, opportunities exist to clarify the core competencies of each research community and to build bridges between them in pursuit of the shared goal of improving user-facing interventions that address misinformation online. This paper attempts to contribute to such bridge-building by posing questions for discussion: How do different incentive structures determine the selection of outcome metrics and the design of research studies by academics and platform researchers, given the values and objectives of their respective institutions? What factors affect the evaluation of intervention feasibility for platforms that are not present for academics (for example, platform users' perceptions, measurability at scale, interaction, and longitudinal effects on metrics that are introduced in real-world deployments)? What are the mutually beneficial opportunities for collaboration (such as increased insight-sharing from platforms to researchers about user feedback regarding a diversity of intervention designs). Finally, we introduce a measurement attributes framework to aid development of feasible, meaningful, and replicable metrics for researchers and platform practitioners to consider when developing, testing, and deploying misinformation interventions.