Response to the Netflix Docuseries "Big Vape: The Rise and Fall of JUUL": Mixed Methods Analysis of YouTube Comments Using Qualitative Coding and Topic Modeling.
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引用次数: 0
Abstract
Background: On October 11, 2023, Netflix released the docuseries "Big Vape: The Rise and Fall of JUUL," which chronicled the founding of JUUL, its rise in popularity among youth, and the subsequent public backlash. The official Netflix YouTube channel posted a trailer promoting the docuseries and an official clip from the docuseries. Recent studies have demonstrated the utility of using comments posted under YouTube videos to analyze reactions to the content and discourse around the health topics explored in the video.
Objective: This study aimed to (1) systematically characterize nicotine and tobacco product (NTP)-related comments and replies posted in response to the docuseries trailer and video clip and (2) explore integration of automated topic modeling techniques with traditional human-generated qualitative coding.
Methods: We extracted all comments and replies on the aforementioned YouTube clips 1 month after the docuseries' release (N=532). Research assistants manually double-coded the comments using a systematically developed codebook that assessed for NTP sentiment (pro-NTP, anti-NTP, complex sentiment, or no sentiment) and the presence or absence of specific electronic cigarette (e-cigarette)-related content. Given the substantial amount of comments coded as potential misinformation during the coding process, we conducted an in-depth qualitative content analysis of all comments coded as potential misinformation. Simultaneously, we used word clustering techniques including structural topic modeling to identify the overarching topics.
Results: Of the 73.8% ( 393/532) relevant comments, 63.6% (250/393) expressed NTP sentiment with 42.8% of these (107/250) expressing pro-NTP sentiment and 18.4% (46/250) expressing complex sentiment. The most frequent content category was potential misinformation (27.5%, 108/393). These 108 comments contained 152 individual pieces of misinformation that were broadly grouped within 6 themes with various numbers of subthemes; the most frequent misinformation theme was that e-cigarette use is completely safe or much safer than smoking (n=80). Other frequently occurring content categories included e-cigarette use is safer than smoking (17.6%, 69/393), and personal experience using e-cigarettes or JUUL (15.5%, 61/393). For topic modeling, we identified 9 topics that we qualitatively assigned into 4 thematic categories: comparisons with other drugs, mentions of government and pharma companies, role of media and parents, and harms associated with nicotine and tobacco products.
Conclusions: To the best of our knowledge, this is the first study to examine viewer reactions to the docuseries about JUUL. Our analysis of YouTube comments offers insight into current sentiment and misinformation regarding NTPs and highlights the potential utility of using mixed methods to analyze NTP-related social media data, and the benefits of integrating computational and human qualitative research to analyze social media perceptions of e-cigarettes. Public health professionals can use our findings to help develop tailored health communication messages to address common sentiment and misconceptions related to JUUL, other e-cigarette products, and new NTP products.
背景:2023年10月11日,Netflix发布了纪录片《大电子烟:JUUL的兴衰》(Big Vape: the Rise and Fall of JUUL),记录了JUUL的成立、在年轻人中的流行以及随后的公众反弹。Netflix的官方YouTube频道发布了宣传这部纪录片的预告片和纪录片的官方剪辑。最近的研究表明,使用YouTube视频下发布的评论来分析对视频中所探讨的健康主题的内容和话语的反应是有用的。目的:本研究旨在(1)系统表征纪录片预告片和视频片段中尼古丁和烟草制品(NTP)相关评论和回复;(2)探索自动化主题建模技术与传统人工生成定性编码的融合。方法:我们提取上述YouTube视频在纪录片发布1个月后的所有评论和回复(N=532)。研究助理使用系统开发的代码本对评论进行了手动双重编码,该代码本评估了NTP情绪(支持NTP、反对NTP、复杂情绪或没有情绪)以及是否存在特定的电子烟相关内容。考虑到编码过程中编码为潜在错误信息的大量评论,我们对所有编码为潜在错误信息的评论进行了深入的定性内容分析。同时,我们使用包括结构主题建模在内的词聚类技术来识别总体主题。结果:在73.8%(393/532)的相关评论中,63.6%(250/393)表达了NTP的观点,其中42.8%(107/250)表达了支持NTP的观点,18.4%(46/250)表达了复杂的观点。最常见的内容类别是潜在的错误信息(27.5%,108/393)。这108条评论包含152条单独的错误信息,这些错误信息大致分为6个主题和不同数量的副主题;最常见的错误信息主题是使用电子烟是完全安全的,或者比吸烟安全得多(n=80)。其他频繁出现的内容类别包括使用电子烟比吸烟更安全(17.6%,69/393),以及使用电子烟或JUUL的个人经历(15.5%,61/393)。对于主题建模,我们确定了9个主题,并定性地将其划分为4个主题类别:与其他药物的比较,提到政府和制药公司,媒体和家长的角色,以及与尼古丁和烟草产品相关的危害。结论:据我们所知,这是第一个研究观众对JUUL纪录片反应的研究。我们对YouTube评论的分析提供了关于ntp的当前情绪和错误信息的见解,并强调了使用混合方法分析ntp相关社交媒体数据的潜在效用,以及整合计算和人类定性研究来分析社交媒体对电子烟的看法的好处。公共卫生专业人员可以利用我们的研究结果来帮助制定量身定制的健康沟通信息,以解决与JUUL、其他电子烟产品和新的NTP产品相关的共同情绪和误解。