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

被引:0
|
作者
Correia, Jorge Cesar [1 ,2 ]
Ahmad, Sarmad Shaharyar [3 ]
Waqas, Ahmed [4 ]
Meraj, Hafsa [5 ]
Pataky, Zoltan [1 ,2 ]
机构
[1] Univ Hosp Geneva, WHO Collaborating Ctr, Unit Therapeut Patient Educ, Chemin Venel 7, CH-1206 Geneva, Switzerland
[2] Univ Geneva, Chemin Venel 7, CH-1206 Geneva, Switzerland
[3] Liverpool Hope Univ, Sch Math Comp Sci & Engn, Liverpool, England
[4] Univ Liverpool, Inst Populat Hlth, Dept Primary Care & Mental Hlth, Liverpool, England
[5] Greater Manchester Mental Hlth NHS Fdn Trust, Salford, England
关键词
obesity; Twitter; infodemic; attitude; opinion; perception; perspective; obese; weight; overweight; social media; tweet; sentiment; topic modeling; BERT; Bidirectional Encoder Representations from Transformers; NLP; natural language processing; generalpublic; celebrities; WEIGHT STIGMA; OUTCOMES; IMPACT;
D O I
10.2196/52142
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: 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. Objective: 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).Methods: 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. Results: 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 theUnited 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. Conclusions: 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
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Nursing students' emotions, educational concerns, and the impact of study careers and professional futures during the COVID-19 pandemic: a cross-sectional study
    Song, Miaojing
    Zhang, Lin
    Ji, Qiqi
    Ji, Pengjuan
    Xu, Jiashuang
    Chen, Yian
    Guo, Leilei
    BMC MEDICAL EDUCATION, 2024, 24 (01)
  • [42] Nursing students’ emotions, educational concerns, and the impact of study careers and professional futures during the COVID-19 pandemic: a cross-sectional study
    Miaojing Song
    Lin Zhang
    Qiqi Ji
    Pengjuan Ji
    Jiashuang Xu
    Yian Chen
    Leilei Guo
    BMC Medical Education, 24
  • [43] Predictors of Cyberchondria During the COVID-19 Pandemic: Cross-sectional Study Using Supervised Machine Learning
    Infanti, Alexandre
    Starcevic, Vladan
    Schimmenti, Adriano
    Khazaal, Yasser
    Karila, Laurent
    Giardina, Alessandro
    Flayelle, Maeva
    Razavi, Seyedeh Boshra Hedayatzadeh
    Baggio, Stephanie
    Vogele, Claus
    Billieux, Joel
    JMIR FORMATIVE RESEARCH, 2023, 7
  • [44] Clinician satisfaction and experience using teleconsultation during the COVID-19 pandemic in Pakistan: A cross-sectional study
    Zahoor, Al-Wardha
    Khan, Zainab
    Khan, Amna
    Qamar, Naveed
    Farooqui, Sumaira
    Allana, Raheel
    INTERNATIONAL ARCHIVES OF HEALTH SCIENCES, 2023, 10 (01) : 7 - 13
  • [45] Media use, positive and negative emotions, and stress levels of adults during COVID-19 pandemic in Turkey: A cross-sectional study
    Akca, Aysegul
    Ayaz-Alkaya, Sultan
    INTERNATIONAL JOURNAL OF NURSING PRACTICE, 2022, 28 (02)
  • [46] The mediating role of regulatory emotional self-efficacy on negative emotions during the COVID-19 pandemic: A cross-sectional study
    Sui, Weijing
    Gong, Xiaoyan
    Zhuang, Yiyu
    INTERNATIONAL JOURNAL OF MENTAL HEALTH NURSING, 2021, 30 (03) : 757 - 769
  • [47] Repercussions of the COVID-19 pandemic on athletes: a cross-sectional study
    Lopes, Lucas R.
    Miranda, Vitor A. R.
    Goes, Rodrigo A.
    Souza, Gabriel G. A.
    Souza, Giuliana R.
    Rocha, Jessica C. S.
    Cossich, Victor R. A.
    Perini, Jamila A.
    BIOLOGY OF SPORT, 2021, 38 (04) : 703 - 711
  • [48] COVID-19 Assessment and Testing in Rural Communities During the Pandemic: Cross-sectional Analysis
    Fitzsimon, Jonathan
    Gervais, Oliver
    Lanos, Chelsea
    JMIR PUBLIC HEALTH AND SURVEILLANCE, 2022, 8 (02):
  • [49] Cross-Sectional Analysis of the Complaints an Emergency Department Attendances During COVID-19 Pandemic
    Ghaffar, Ali
    Garlapati, Rajendar
    CUREUS JOURNAL OF MEDICAL SCIENCE, 2020, 12 (12)
  • [50] Emergency care and the patient experience: Using sentiment analysis and topic modeling to understand the impact of the COVID-19 pandemic
    Chekijian, Sharon
    Li, Huan
    Fodeh, Samah
    HEALTH AND TECHNOLOGY, 2021, 11 (05) : 1073 - 1082