Disrupting the COVID-19 Misinfodemic With Network Interventions: Network Solutions for Network Problems.

Area of Science:

• Public Health
• Network Science
• Information Science

Background:

• The COVID-19 pandemic is complicated by a surge in viral misinformation, termed the "misinfodemic."
• This misinformation negatively impacts public health outcomes and health behavior.
• Existing research characterizes misinformation but lacks disruption strategies.

Purpose of the Study:

• To propose a framework for disrupting COVID-19 misinformation dynamics.
• To identify network-based intervention strategies for combating the "misinfodemic."

Main Methods:

• Conceptualizing misinformation spread as a networked phenomenon.
• Proposing five classes of social network interventions.
• Identifying key features of information environments for intervention.

Main Results:

• Five distinct yet interdependent classes of social network interventions are proposed.
• These interventions target specific features of information environments to disrupt misinformation.
• The strategies offer a roadmap for addressing misinformation during global health crises.

Conclusions:

• Network interventions are crucial for disrupting the diffusion and persistence of health misinformation.
• Addressing the "misinfodemic" requires strategic interventions within social networks.
• The proposed strategies provide a foundation for future research and practical application in public health communication.