Cracking the 'Meta' Code: Advanced Machine Learning-Based Sentiment Analysis of Water Fluoridation Debates on Facebook and Instagram

Social media platforms like Facebook and Instagram are pivotal in shaping public opinion on health interventions, including Community Water Fluoridation (CWF). Despite its recognition as a safe and effective public health measure, CWF remains a polarising topic, with misinformation on these platforms contributing to public mistrust. This study collected 109,117 Facebook and Instagram posts from 2014 to 2023 to examine public sentiment surrounding CWF. The analysis revealed a mix of opinions, with 42.1% positive, 39.1% negative, and 18.8% neutral sentiments. Trends highlighted a surge in negative sentiment during 2017–2019, likely influenced by misinformation and significant public events, while positive sentiment has gradually regained ground in recent years. Key themes included health benefits, safety concerns, and government trust, with positive discussions emphasising CWF’s role in public health and negative discussions focusing on risks and chemical exposure. The study used advanced sentiment analysis models to highlight the importance of monitoring public discourse and addressing misinformation to build trust and support for evidence-based health policies like CWF. These findings provide digital data-driven insights for public health communication strategies to enhance community understanding and acceptance of vital health interventions.