Mapping the "X" Debate: Water Fluoridation Sentiment Analysis With Advanced Machine Learning.

ABSTRACT:

Objectives

This study aimed to examine public sentiment regarding community water fluoridation (CWF) using data from "X" (formerly Twitter) over the past decade. The goal was to understand public opinion trends and identify opportunities for targeted public health communication.

Methods

We conducted a sentiment analysis utilizing a natural language processing technique. Specifically, we applied the Sentiment Intensity Analyzer tool to classify tweets related to CWF into negative, positive, or neutral categories. Additionally, a word co-occurrence network analysis was performed to explore key discussion themes. We also compared machine learning models to assess their accuracy in classifying tweet sentiments.

Results

Analysis of the tweets revealed a balanced distributi

SUBMITTER: Torwane N 

PROVIDER: S-EPMC12418723 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature