Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Nov 24, 2022
Date Accepted: Jun 7, 2023
Analysis of fluoride-free content on Twitter: A topic modeling study
ABSTRACT
Background:
Online misinformation concerning the side effects of fluoridated oral care products and tap water contributes to the onset and propagation of untrue beliefs that culminate in anti-fluoridation movements.
Objective:
This study aimed to analyze the fluoride-related misinformation on Twitter automatically.
Methods:
21,169 tweets published in English between May 2016 and May 2022 that included the keyword “fluoride-free” were retrieved by Twitter API. Latent Dirichlet Allocation (LDA) topic modeling was applied to identify the salient terms and topics. The similarity between topics was calculated through an intertopic distance map. The total count of misinformation records for each topic and their relevance over time were determined.
Results:
Utilizing a coherence score of 0.542, a total of 3 distinctly distributed salient topics emerged from the LDA topic modeling analysis. Results show that fluoride-related misinformation on Twitter was mainly associated with people’s perception of a healthy lifestyle, followed by the consumption of natural and organic oral care products and recommendations of fluoride-free products and measures. Interest in false content decreased between 2016 and 2019 and increased again after 2020.
Conclusions:
Fluoride misinformation found on Twitter related to a healthy lifestyle. This misleading content probably contributed to the popularization of fluoride-free oral care products and the suspension of community water fluoridation programs. Strategies are needed to address and limit the spread of misinformation on social media.
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Copyright
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