Tingfen Ji, Zhao Liu, Zheng Su, Xin Xia, Yi Liu, Ying Xie, Zhenxiao Huang, Xinmei Zhou, Min Wang, Anqi Cheng, Qingqing Song, Yuxin Shi, Shunyi Shi, Aihemaiti Ailifeire, Jiahui He, Yingman Gao, Liang Zhao, Liyan Wu, Dan Xiao, Chen Wang
{"title":"E-Cigarette Narratives of User-Generated Posts on Xiaohongshu in China: Content Analysis.","authors":"Tingfen Ji, Zhao Liu, Zheng Su, Xin Xia, Yi Liu, Ying Xie, Zhenxiao Huang, Xinmei Zhou, Min Wang, Anqi Cheng, Qingqing Song, Yuxin Shi, Shunyi Shi, Aihemaiti Ailifeire, Jiahui He, Yingman Gao, Liang Zhao, Liyan Wu, Dan Xiao, Chen Wang","doi":"10.2196/71173","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Social media platforms have become influential spaces for disseminating information about electronic cigarettes (e-cigarettes). Concerns persist about the spread of misleading content, particularly among social media vulnerable groups. Xiaohongshu (RedNote), widely used by Chinese youth, plays a growing role in shaping e-cigarette perceptions. Understanding the narratives circulating on this platform is essential for identifying misinformation, assessing public perception, and guiding future health communication strategies.</p><p><strong>Objective: </strong>This study aimed to analyze the content, topics, user engagement, and sentiment trends of e-cigarette-related posts on Xiaohongshu and to assess the factors that influence engagement.</p><p><strong>Methods: </strong>E-cigarette-related posts published on Xiaohongshu between January 2020 and November 2024 were collected using web scraping, based on a predefined keyword list and a time-stratified random sampling strategy. Posts were categorized into 4 themes: advertising promotion, health hazards, usage interaction, and others. High-frequency keywords were extracted, and representative quotes were included to illustrate user perspectives across each category. Sentiment analysis was performed on posts in the usage interaction category to assess public attitudes. We defined 4 sentiment categories: positive, negative, neutral, and mixed. Logistic regression was conducted to explore the effects of post type, content length, and thematic classification on user engagement metrics such as likes, saves, and comments.</p><p><strong>Results: </strong>A total of 1729 posts were included and analyzed. Usage interaction posts were the most common (681/1729, 39.39%), with keywords such as \"experience,\" \"regulations,\" and \"quit smoking\" dominating this category. Advertising promotion posts (512/1729, 29.61%) frequently used terms like \"flavor,\" \"fashion,\" and \"design\" to attract younger users. Health hazards posts (311/1729, 17.99%) highlighted risks with keywords like \"nicotine,\" \"addiction,\" and \"secondhand smoke,\" while others included policy and industry updates. Representative quotes highlighted typical concerns about aesthetics, health risks, and cessation struggles. Health hazards posts garnered the highest engagement in terms of likes and saves, despite their limited presence (odds ratio [OR] 1.498, 95% CI 1.099-2.042, P=.01). Video posts significantly outperformed text-image posts in generating comments (OR 2.624, 95% CI 2.017-3.439, P<.001). Sentiment analysis of the usage interaction posts (n=681) revealed that 53.45% (364/681) were positive, highlighting reduced harm, convenience, or flavor preferences. Negative sentiment was observed in 33.48% (228/681) of posts, often expressing concerns about addiction and health risks. Mixed sentiments appeared in 6.90% (47/681), acknowledging both pros and cons. In addition, 6.17% (42/681) of posts were classified as neutral without evident emotional tone.</p><p><strong>Conclusions: </strong>The findings underscore the dual role of Xiaohongshu as a platform for both e-cigarette promotion and public discourse. Misleading marketing targeting vulnerable groups, such as adolescents, remains a critical issue. However, the strong user response to health-related content suggests that social media platforms could be leveraged for effective health education. Strengthened regulatory oversight and educational campaigns leveraging engaging content formats are urgently needed to counter misinformation and protect public health.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e71173"},"PeriodicalIF":5.8000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12244743/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Internet Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/71173","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Social media platforms have become influential spaces for disseminating information about electronic cigarettes (e-cigarettes). Concerns persist about the spread of misleading content, particularly among social media vulnerable groups. Xiaohongshu (RedNote), widely used by Chinese youth, plays a growing role in shaping e-cigarette perceptions. Understanding the narratives circulating on this platform is essential for identifying misinformation, assessing public perception, and guiding future health communication strategies.
Objective: This study aimed to analyze the content, topics, user engagement, and sentiment trends of e-cigarette-related posts on Xiaohongshu and to assess the factors that influence engagement.
Methods: E-cigarette-related posts published on Xiaohongshu between January 2020 and November 2024 were collected using web scraping, based on a predefined keyword list and a time-stratified random sampling strategy. Posts were categorized into 4 themes: advertising promotion, health hazards, usage interaction, and others. High-frequency keywords were extracted, and representative quotes were included to illustrate user perspectives across each category. Sentiment analysis was performed on posts in the usage interaction category to assess public attitudes. We defined 4 sentiment categories: positive, negative, neutral, and mixed. Logistic regression was conducted to explore the effects of post type, content length, and thematic classification on user engagement metrics such as likes, saves, and comments.
Results: A total of 1729 posts were included and analyzed. Usage interaction posts were the most common (681/1729, 39.39%), with keywords such as "experience," "regulations," and "quit smoking" dominating this category. Advertising promotion posts (512/1729, 29.61%) frequently used terms like "flavor," "fashion," and "design" to attract younger users. Health hazards posts (311/1729, 17.99%) highlighted risks with keywords like "nicotine," "addiction," and "secondhand smoke," while others included policy and industry updates. Representative quotes highlighted typical concerns about aesthetics, health risks, and cessation struggles. Health hazards posts garnered the highest engagement in terms of likes and saves, despite their limited presence (odds ratio [OR] 1.498, 95% CI 1.099-2.042, P=.01). Video posts significantly outperformed text-image posts in generating comments (OR 2.624, 95% CI 2.017-3.439, P<.001). Sentiment analysis of the usage interaction posts (n=681) revealed that 53.45% (364/681) were positive, highlighting reduced harm, convenience, or flavor preferences. Negative sentiment was observed in 33.48% (228/681) of posts, often expressing concerns about addiction and health risks. Mixed sentiments appeared in 6.90% (47/681), acknowledging both pros and cons. In addition, 6.17% (42/681) of posts were classified as neutral without evident emotional tone.
Conclusions: The findings underscore the dual role of Xiaohongshu as a platform for both e-cigarette promotion and public discourse. Misleading marketing targeting vulnerable groups, such as adolescents, remains a critical issue. However, the strong user response to health-related content suggests that social media platforms could be leveraged for effective health education. Strengthened regulatory oversight and educational campaigns leveraging engaging content formats are urgently needed to counter misinformation and protect public health.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.