Electronic Cigarette Users' Perspective on the COVID-19 Pandemic: Observational Study Using Twitter Data

Abstract

Background Previous studies have shown that electronic cigarette (e-cigarette) users might be more vulnerable to COVID-19 infection and could develop more severe symptoms if they contract the disease owing to their impaired immune responses to viral infections. Social media platforms such as Twitter have been widely used by individuals worldwide to express their responses to the current COVID-19 pandemic. Objective In this study, we aimed to examine the longitudinal changes in the attitudes of Twitter users who used e-cigarettes toward the COVID-19 pandemic, as well as compare differences in attitudes between e-cigarette users and nonusers based on Twitter data. Methods The study dataset containing COVID-19–related Twitter posts (tweets) posted between March 5 and April 3, 2020, was collected using a Twitter streaming application programming interface with COVID-19–related keywords. Twitter users were classified into two groups: Ecig group, including users who did not have commercial accounts but posted e-cigarette–related tweets between May 2019 and August 2019, and non-Ecig group, including users who did not post any e-cigarette–related tweets. Sentiment analysis was performed to compare sentiment scores towards the COVID-19 pandemic between both groups and determine whether the sentiment expressed was positive, negative, or neutral. Topic modeling was performed to compare the main topics discussed between the groups. Results The US COVID-19 dataset consisted of 4,500,248 COVID-19–related tweets collected from 187,399 unique Twitter users in the Ecig group and 11,479,773 COVID-19–related tweets collected from 2,511,659 unique Twitter users in the non-Ecig group. Sentiment analysis showed that Ecig group users had more negative sentiment scores than non-Ecig group users. Results from topic modeling indicated that Ecig group users had more concerns about deaths due to COVID-19, whereas non-Ecig group users cared more about the government’s responses to the COVID-19 pandemic. Conclusions Our findings show that Twitter users who tweeted about e-cigarettes had more concerns about the COVID-19 pandemic. These findings can inform public health practitioners to use social media platforms such as Twitter for timely monitoring of public responses to the COVID-19 pandemic and educating and encouraging current e-cigarette users to quit vaping to minimize the risks associated with COVID-19.

The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States

“…Age and gender would be collected if the image only contains one face. As reported in a previous study [15], face++ has an accuracy of 93% in predicting gender. Age is much harder to be accurately determined, and the accuracy is 41%.…”

“…We used the Twitter streaming API to collect COVID-19 related Twitter posts (tweets) between March 5 th , 2020 and January 31 st , 2021 using COVID-19-related keywords, except from May 18 th , 2020 to May 19 th , 2020, and from August 24 th , 2020 to September 14 th , 2020 due to technical issues. The COVID-19 related keywords include abbreviations and aliases ("corona", "covid19", "covid", "coronavirus", "NCOV") [15]. The dataset was filtered with health-related keywords from seven health-related categories including mental health, cardiovascular, respiratory, neurological, psychological, digestive, and other [16,17].…”

Mental Health Concerns Related to the COVID-19 Pandemic on Twitter in the UK

“…We collected COVID-19-related tweets posted between March 5, 2020 and January 31, 2021 through the Twitter Streaming API using the keywords ("corona", "covid19", "covid", "coronavirus", and "ncov") 12 . The Twitter data from May 18 to May 20, 2020, and from August 25 to September 14, 2020 were missing due to some technical failure.…”

A high-resolution temporal and geospatial content analysis of Twitter posts related to the COVID-19 pandemic

“…Some approaches exploited the geolocation metadata available in Twitter to derive a social mobility index [ 5 ] or predict risk of pandemic for a region [ 6 ]. Other studies investigated the content of limited number of tweets published by specific official health organizations [ 7 ]; of specific social media movements (e.g., the Free Open Access Medical Education twitter movement #FOAMed) [ 8 ]; and of specific user groups, for example, people with arthritis [ 9 ], electronic cigarette users [ 10 ], and people interested in plastic and esthetic surgery [ 11 ].…”