Mapping the “X” Debate: Water Fluoridation Sentiment Analysis With Advanced Machine Learning

Our findings highlight the polarized nature of public sentiment toward CWF and the temporal fluctuations in public engagement. These insights can inform public health policymakers in developing timely, targeted communication strategies. Specifically, efforts to engage neutral audiences through transparent messaging and counter misinformation during key periods may strengthen public trust in CWF. The application of machine learning in this analysis underscores its value in enhancing real-time monitoring and supporting evidence-based public health strategies.