Exploring Public Emotions on Obesity During the COVID-19 Pandemic Using Sentiment Analysis and Topic Modeling: Cross-Sectional Study.

Exploring Public Emotions on Obesity During the COVID-19 Pandemic Using Sentiment Analysis and Topic Modeling: Cross-Sectional Study.

Publication date: Oct 11, 2024

Obesity is a chronic, multifactorial, and relapsing disease, affecting people of all ages worldwide, and is directly related to multiple complications. Understanding public attitudes and perceptions toward obesity is essential for developing effective health policies, prevention strategies, and treatment approaches. This study investigated the sentiments of the general public, celebrities, and important organizations regarding obesity using social media data, specifically from Twitter (subsequently rebranded as X). The study analyzes a dataset of 53,414 tweets related to obesity posted on Twitter during the COVID-19 pandemic, from April 2019 to December 2022. Sentiment analysis was performed using the XLM-RoBERTa-base model, and topic modeling was conducted using the BERTopic library. The analysis revealed that tweets regarding obesity were predominantly negative. Spikes in Twitter activity correlated with significant political events, such as the exchange of obesity-related comments between US politicians and criticism of the United Kingdom’s obesity campaign. Topic modeling identified 243 clusters representing various obesity-related topics, such as childhood obesity; the US President’s obesity struggle; COVID-19 vaccinations; the UK government’s obesity campaign; body shaming; racism and high obesity rates among Black American people; smoking, substance abuse, and alcohol consumption among people with obesity; environmental risk factors; and surgical treatments. Twitter serves as a valuable source for understanding obesity-related sentiments and attitudes among the public, celebrities, and influential organizations. Sentiments regarding obesity were predominantly negative. Negative portrayals of obesity by influential politicians and celebrities were shown to contribute to negative public sentiments, which can have adverse effects on public health. It is essential for public figures to be mindful of their impact on public opinion and the potential consequences of their statements.

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Concepts Keywords
December attitude
Library BERT
Obesity celebrities
President COVID-19
Twitter Cross-Sectional Studies
Emotions
general public
Humans
infodemic
natural language processing
NLP
obese
Obesity
obesity
opinion
overweight
Pandemics
perception
perspective
Public Opinion
SARS-CoV-2
sentiment
Social Media
social media
topic modeling
tweet
Twitter
United Kingdom
United States
weight

Semantics

Type Source Name
disease MESH Obesity
disease MESH COVID-19 Pandemic
disease MESH complications
disease MESH childhood obesity
disease MESH substance abuse
drug DRUGBANK Ethanol
disease MESH overweight
disease MESH cancers
disease MESH depression
disease MESH anxiety disorders
disease MESH psychiatric diseases
disease MESH bullying
drug DRUGBANK Alpha-1-proteinase inhibitor
disease IDO process
disease IDO country
drug DRUGBANK Isoxaflutole
disease IDO algorithm
disease MESH privacy
disease MESH death
disease MESH morbidities
disease MESH educational attainment
disease MESH comorbidity
disease MESH high blood pressure
disease MESH sleep apnea
disease MESH inflammation
drug DRUGBANK Medical air
disease MESH sleep quality
drug DRUGBANK Coenzyme M
disease MESH Emergency
disease MESH asthma
pathway KEGG Asthma
drug DRUGBANK Tropicamide
disease MESH central obesity
drug DRUGBANK Tromethamine
disease MESH diabetes mellitus
drug DRUGBANK Guanosine
drug DRUGBANK Silver
pathway REACTOME Release
pathway REACTOME Reproduction

Original Article

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