THE IMPACT OF SOCIAL MEDIA ALGORITHMS ON THE RETENTION OF VACCINE-RELATED MISINFORMATION
Department: PUBLIC HEALTH |
Price: ₦5,000.00
Project Overview
This research examines how social media algorithms contribute to the retention of vaccine-related misinformation through systematic analysis of recent literature. Findings reveal that algorithmic mechanisms—including personalized recommendations, engagement optimization, and echo chamber formation—systematically amplify misleading vaccine content by exploiting cognitive biases such as confirmation bias and negativity bias (Vosoughi et al., 2018; Patton, 2021). The study demonstrates that algorithmic curation creates information environments resistant to correction, with user-generated corrections proving more influential in shaping social norms than algorithmic corrections (Shanker et al., 2025). Effective mitigation requires comprehensive approaches combining algorithmic redesign, pre-bunking strategies, and multi-stakeholder collaboration to promote accurate health information while respecting free expression principles.
Abstract / Chapter One Preview
ABSTRACT
The proliferation of vaccine-related misinformation through social media platforms represents a significant threat to global public health, undermining vaccination efforts and contributing to preventable disease outbreaks. Central to this challenge is the role of platform algorithms, which are designed to maximize user engagement but inadvertently amplify and sustain misleading content. This research examines the mechanisms through which social media algorithms facilitate the retention of vaccine-related misinformation, drawing upon a comprehensive theoretical framework that integrates concepts from cognitive psychology, media studies, and public health communication. Through analysis of algorithmic curation mechanisms including recommendation systems, personalization, and engagement optimization, the study demonstrates how these technical features create echo chambers, reinforce confirmation bias, and exploit negativity bias to enhance misinformation retention. The findings reveal that algorithmic amplification of vaccine misinformation operates through multiple pathways: (1) the creation of information environments that limit exposure to corrective information, (2) the preferential promotion of emotionally charged and conspiratorial content, and (3) the formation of algorithmically reinforced communities that strengthen anti-vaccine identity. Furthermore, this research evaluates existing algorithmic correction strategies and their effectiveness in combating misinformation retention. The study concludes by proposing a multi-stakeholder framework for mitigating the harmful effects of algorithmic amplification while respecting principles of free expression, with implications for platform governance, public health communication, and future research directions.
Keywords: social media algorithms, vaccine misinformation, misinformation retention, echo chambers, algorithmic amplification, public health communication, vaccine hesitancy
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