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使用情感分析和主题建模探究 COVID-19 大流行期间公众对肥胖的情绪:横断面研究。

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

机构信息

Unit of Therapeutic Patient Education, WHO Collaborating Center, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.

School of Mathematics, Computer Science & Engineering, Liverpool Hope University, Liverpool, United Kingdom.

出版信息

J Med Internet Res. 2024 Oct 11;26:e52142. doi: 10.2196/52142.

Abstract

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 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.

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.

摘要

背景

肥胖是一种慢性、多因素且易复发的疾病,影响着全球各个年龄段的人群,与多种并发症直接相关。了解公众对肥胖的态度和看法对于制定有效的健康政策、预防策略和治疗方法至关重要。

目的

本研究通过社交媒体数据(具体来自 Twitter,后更名为 X)调查了普通公众、名人和重要组织对肥胖的看法。

方法

该研究分析了 2019 年 4 月至 2022 年 12 月期间在 Twitter 上发布的与肥胖相关的 53414 条推文,使用 XLM-RoBERTa-base 模型进行情感分析,并使用 BERTopic 库进行主题建模。

结果

分析表明,与肥胖相关的推文主要是负面的。Twitter 活跃度的峰值与重大政治事件相关,例如美国政治家之间的肥胖相关评论交流以及对英国肥胖运动的批评。主题建模确定了 243 个代表各种肥胖相关主题的簇,例如儿童肥胖;美国总统的肥胖斗争;COVID-19 疫苗接种;英国政府的肥胖运动;身体羞辱;黑人群体中的种族主义和高肥胖率;肥胖人群中的吸烟、药物滥用和酗酒;环境风险因素;以及手术治疗。

结论

Twitter 是了解公众、名人和有影响力组织对肥胖相关情绪和态度的宝贵资源。与肥胖相关的情绪主要是负面的。有影响力的政治家和名人对肥胖的负面描述被证明会导致公众情绪负面,这可能对公共健康产生不利影响。公众人物必须意识到自己对舆论的影响以及言论的潜在后果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a44/11512131/01ddfed9338c/jmir_v26i1e52142_fig1.jpg

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