Center for Tobacco Control Research and Education, University of California, San Francisco, California, United States of America.
Department of Mathematics, University of California, Davis, California, United States of America.
PLoS One. 2021 Dec 8;16(12):e0260290. doi: 10.1371/journal.pone.0260290. eCollection 2021.
With the spread of COVID-19, significant concerns have been raised about the potential increased risk for electronic cigarette (e-cigarette) users for COVID-19 infection and related syndromes. Social media is an increasingly popular source for health information dissemination and discussion, and can affect health outcomes.
This study aims to identify the topics in the public vaping discussion in COVID-19-related Twitter posts in order to get insight into public vaping-related perceptions, attitudes and concerns, and to discern possible misinformation and misconceptions around vaping in the COVID-19 pandemic.
Using the tweets ID database maintained by Georgia State University's Panacea Lab, we downloaded the tweets related to COVID-19 from March 11, 2020, when the World Health Organization declared COVID-19 a pandemic, to February 12, 2021. We used R to analyze the tweets that contained a list of 79 keywords related to vaping. After removing duplicates and tweets created by faked accounts or bots, the final data set consisted of 11,337 unique tweets from 7,710 different users. We performed the latent Dirichlet allocation (LDA) algorithm for topic modeling and carried out a sentiment analysis.
Despite fluctuations, the number of daily tweets was relatively stable (average number of daily tweets = 33.4) with a sole conspicuous spike happening on a few days after August 11, 2020 when a research team published findings that teenagers and young adults who vape face a much higher risk of COVID-19 infection than their peers who do not vape. Topic modeling generated 8 topics: linkage between vaping and risk of COVID-19 infection, vaping pneumonia and the origin of COVID-19, vaping and spread of COVID-19, vaping regulation, calling for quitting vaping, protecting youth, similarity between e-cigarette or vaping-associated lung injury (EVALI) and COVID-19, and sales information. Daily sentiment scores showed that the public sentiment was predominantly negative, but became slightly more positive over the course of the study time period.
While some content in the public discourse on vaping before the COVID-19 pandemic continued in Twitter posts during the COVID-19 time period, new topics emerged. We found a substantial amount of anti-vaping discussion and dominantly negative sentiment around vaping during COVID-19, a sharp contrast to the predominantly pro-vaping voice on social media in the pre-COVID-19 period. Continued monitoring of social media conversations around vaping is needed, and the public health community may consider using social media platforms to actively convey scientific information around vaping and vaping cessation.
随着 COVID-19 的传播,人们对电子烟(e-cigarette)使用者感染 COVID-19 及相关综合征的风险增加表示了极大的关注。社交媒体是健康信息传播和讨论的一个越来越受欢迎的来源,它可以影响健康结果。
本研究旨在确定与 COVID-19 相关的 Twitter 帖子中公众对电子烟讨论的主题,以便深入了解公众对电子烟的看法、态度和关注,并发现 COVID-19 大流行期间围绕电子烟的可能错误信息和误解。
利用佐治亚州立大学 Panacea 实验室维护的推文 ID 数据库,我们从 2020 年 3 月 11 日世界卫生组织宣布 COVID-19 为大流行开始,到 2021 年 2 月 12 日下载了与 COVID-19 相关的推文。我们使用 R 分析包含 79 个与电子烟相关的关键词列表的推文。在去除重复推文和由虚假账户或机器人创建的推文后,最终数据集由来自 7710 个不同用户的 11337 条独特推文组成。我们对主题建模进行了潜在狄利克雷分配(LDA)算法,并进行了情感分析。
尽管有波动,但每日推文数量相对稳定(平均每日推文数量=33.4),仅在 2020 年 8 月 11 日之后的几天内出现了一个明显的峰值,当时一个研究小组发表了一项研究结果,表明吸电子烟的青少年和年轻人感染 COVID-19 的风险比不吸电子烟的同龄人高得多。主题建模生成了 8 个主题:电子烟与 COVID-19 感染风险之间的联系、电子烟肺炎与 COVID-19 的起源、电子烟与 COVID-19 的传播、电子烟管制、呼吁戒烟、保护青少年、电子烟或蒸气相关肺损伤(EVALI)与 COVID-19 的相似性,以及销售信息。每日情感评分显示,公众情绪主要为负面,但在研究期间略有好转。
虽然在 COVID-19 大流行之前,关于电子烟的公众讨论中有一些内容在 COVID-19 期间的 Twitter 帖子中继续存在,但也出现了一些新的主题。我们发现,在 COVID-19 期间,关于电子烟的讨论中存在大量反电子烟内容,情绪普遍负面,与 COVID-19 前社交媒体上主要支持电子烟的声音形成鲜明对比。需要继续监测社交媒体上关于电子烟的对话,公共卫生界可能会考虑利用社交媒体平台积极传达关于电子烟和戒烟的科学信息。