Hookah-Related Posts to Twitter From 2017 to 2018: Thematic Analysis

Spanish-Language Tobacco-Related Posts on Twitter: Content Analysis

INTRODUCTION

Twitter data have been used to surveil public sentiment about tobacco products; however, most tobacco-related Twitter research has been conducted with English-language posts. There is a gap in the literature on tobacco-related discussions on Twitter in languages other than English. This study summarized tobacco-related discussions in Spanish on Twitter.

METHODS

A set of Spanish terms reflecting electronic cigarettes (eg, "cigarillos electrónicos"), cigarettes (eg, "pitillo"), and cigars (eg, "cigaro") were identified. A content analysis of tweets (n = 1352) drawn from 2021 was performed to examine themes and sentiment. An initial codebook was developed in English then translated to Spanish and then translated back to English by a bilingual (Spanish and English) member of the research team. Two bilingual members of the research team coded the tweets into themes and sentiment.

RESULTS

Themes in the tweets included (1) product promotion (n = 168, 12.4%), (2) health warnings (n = 161, 11.9%), (3) tobacco use (n = 136, 10.1%), (4) health benefits of vaping (n = 58, 4.3%), (5) cannabis use (n = 50, 3.7%), (6) cessation (n = 47, 3.5%), (7) addiction (n = 33, 2.4%), (8) policy (n = 27, 2.0%), and (9) polysubstance use (n = 12, 0.9%). Neutral (n = 955, 70.6%) was the most common category of sentiment observed in the data.

CONCLUSIONS

Tobacco products are discussed in multiple languages on Twitter and can be summarized by bilingual research teams. Future research should determine if Spanish-speaking individuals are frequently exposed to pro-tobacco content on social media and if such exposure increases susceptibility to use tobacco among never users or sustained use among current users.

IMPLICATIONS

Spanish-language pro-tobacco content exists on Twitter, which has implications for Spanish-speaking individuals who may be exposed to this content. Spanish-language pro-tobacco-related posts may help normalize tobacco use among Spanish-speaking populations. As a result, anti-tobacco tweets in Spanish may be necessary to counter areas of the online environment that can be considered pro-tobacco.

#TurntTrending: a systematic review of substance use portrayals on social media platforms

AIMS

There is a growing body of literature exploring the types of substance-related content and their portrayals on various social media platforms. We aimed to summarize how content related to substances is portrayed on various social media platforms.

METHODS

This systematic review was pre-registered on PROSPERO (ref: CRD42021291853). A comprehensive search was conducted in the databases of PubMed, Scopus, PsycINFO and Web of Science in April 2021. Original qualitative studies published post-2004 that included thematic and sentiment analyses of social media content on tobacco, alcohol, psychostimulant, e-cigarette, cannabis, opiate, stimulant/amphetamine, inhalant and novel psychoactive substance were included. Social media platforms were defined as online web- or application-based platforms that allowed users to generate content and interact via 'liking', comment or messaging features. Only studies that included summative and/or thematic content analyses of substance-related social media content were included.

RESULTS

A total of 73 studies, which covered 15 905 182 substance-related posts on Twitter, YouTube, Instagram, Pinterest, TikTok and Weibo, were identified. A total of 76.3% of all substance-related content was positive in its depiction of substance use, with 20.2% of content depicting use negatively. Sentiment regarding opiate use however was commonly negative (55.5%). Most studies identified themes relating to Health, Safety and Harms (65.0%) of substance use. Themes relating to Promotions/Advertisements (63.3%), Informative content (55.0%) and Use behaviours (43.3%) were also frequently identified.

CONCLUSIONS

Substance-related content that promotes engagement with substance use or actively depicts use appears to be widely available on social media. The large public presence of this content may have concerning influences on attitudes, behaviours and risk perceptions relating to substance use, particularly among the most vulnerable and heaviest users of social media-adolescents and young adults.

Using Natural Language Processing to Explore "Dry January" Posts on Twitter: Longitudinal Infodemiology Study

BACKGROUND

Dry January, a temporary alcohol abstinence campaign, encourages individuals to reflect on their relationship with alcohol by temporarily abstaining from consumption during the month of January. Though Dry January has become a global phenomenon, there has been limited investigation into Dry January participants' experiences. One means through which to gain insights into individuals' Dry January-related experiences is by leveraging large-scale social media data (eg, Twitter chatter) to explore and characterize public discourse concerning Dry January.

OBJECTIVE

We sought to answer the following questions: (1) What themes are present within a corpus of tweets about Dry January, and is there consistency in the language used to discuss Dry January across multiple years of tweets (2020-2022)? (2) Do unique themes or patterns emerge in Dry January 2021 tweets after the onset of the COVID-19 pandemic? and (3) What is the association with tweet composition (ie, sentiment and human-authored vs bot-authored) and engagement with Dry January tweets?

METHODS

We applied natural language processing techniques to a large sample of tweets (n=222,917) containing the term "dry january" or "dryjanuary" posted from December 15 to February 15 across three separate years of participation (2020-2022). Term frequency inverse document frequency, k-means clustering, and principal component analysis were used for data visualization to identify the optimal number of clusters per year. Once data were visualized, we ran interpretation models to afford within-year (or within-cluster) comparisons. Latent Dirichlet allocation topic modeling was used to examine content within each cluster per given year. Valence Aware Dictionary and Sentiment Reasoner sentiment analysis was used to examine affect per cluster per year. The Botometer automated account check was used to determine average bot score per cluster per year. Last, to assess user engagement with Dry January content, we took the average number of likes and retweets per cluster and ran correlations with other outcome variables of interest.

RESULTS

We observed several similar topics per year (eg, Dry January resources, Dry January health benefits, updates related to Dry January progress), suggesting relative consistency in Dry January content over time. Although there was overlap in themes across multiple years of tweets, unique themes related to individuals' experiences with alcohol during the midst of the COVID-19 global pandemic were detected in the corpus of tweets from 2021. Also, tweet composition was associated with engagement, including number of likes, retweets, and quote-tweets per post. Bot-dominant clusters had fewer likes, retweets, or quote tweets compared with human-authored clusters.

CONCLUSIONS

The findings underscore the utility for using large-scale social media, such as discussions on Twitter, to study drinking reduction attempts and to monitor the ongoing dynamic needs of persons contemplating, preparing for, or actively pursuing attempts to quit or cut down on their drinking.

Attitudes towards the 'Shisha No Thanks' campaign video: Content analysis of Facebook comments

INTRODUCTION

While social media are commonly used in public health campaigns, there is a gap in our understanding of what happens after the campaign is seen by the target audience. This study aims to understand how the Shisha No Thanks campaign video was received by the Facebook audience by analyzing Facebook comments posted to it. Specifically, this study aims to determine whether the Facebook audience accepted or rejected the campaign’s message.

METHODS

A sample of the Facebook comments was extracted, and the study team, which included cultural support workers, developed content categories consistent with the research question. Each comment was then coded by three team members, and only assigned a category if there was agreement by at least two members.

RESULTS

Of the 4990 comments that were sampled, 9.1% (456) accepted the campaign message, 22.9% (1144) rejected the message, 21.8% (1089) were unclear, and 46.1% (2301) contained only tagged names. Of the sample, 2.8% (138) indicated the commenter took on board the campaign message by expressing an intention to stop smoking shisha, or asking a friend to stop smoking shisha. Of the comments that showed rejection of the campaign, the majority were people dismissing the campaign by laughing at it or expressing pro-shisha sentiments.

CONCLUSIONS

This study demonstrates that conducting content analyses of social media comments can provide important insight into how a campaign message is received by a social media audience.

Analyzing Twitter Chatter About Tobacco Use Within Intoxication-related Contexts of Alcohol Use: "Can Someone Tell Me Why Nicotine is So Fire When You're Drunk?"

INTRODUCTION

Alcohol and tobacco are commonly used together. Social influences within online social networking platforms contribute to youth and young adult substance use behaviors. This study used a sample of alcohol- and tobacco-related tweets to evaluate: (1) sentiment toward co-use of alcohol and tobacco, (2) increased susceptibility to tobacco use when consuming alcohol, and (3) the role of alcohol in contributing to a failed attempt to quit tobacco use.

METHODS

Data were collected from the Twitter API from January 1, 2019 through December 31, 2019 using tobacco-related keywords (e.g., vape, ecig, smoking, juul*) and alcohol-related filters (e.g., drunk, blackout*). A total of 78,235 tweets were collected, from which a random subsample (n = 1,564) was drawn for coding. Cohen's Kappa values ranged from 0.66 to 0.99.

RESULTS

Most tweets were pro co-use of alcohol and tobacco (75%). One of every ten tweets reported increased susceptibility to tobacco use when intoxicated. Non-regular tobacco users reported cravings for and tobacco use when consuming alcohol despite disliking tobacco use factors such as the taste, smell, and/or negative health effects. Regular tobacco users reported using markedly higher quantities of tobacco when intoxicated. Individuals discussed the role of alcohol undermining tobacco cessation attempts less often (2.0%), though some who had quit smoking for prolonged periods of time reported reinitiating tobacco use during acute intoxication episodes.

CONCLUSIONS

Tobacco cessation interventions may benefit from including alcohol-focused components designed to educate participants about the association between increased susceptibility to tobacco use when consuming alcohol and the role of alcohol in undermining tobacco cessation attempts.

IMPLICATIONS

Sentiment toward co-use of alcohol and tobacco on Twitter is largely positive. Individuals reported regret about using tobacco, or using more than intended, when intoxicated. Those who had quit smoking or vaping for prolonged periods of time reported reinitiating tobacco use when consuming alcohol. While social media-based tobacco cessation interventions like the Truth Initiative's "Ditch the Juul" campaign demonstrate potential to change tobacco use behaviors, these campaigns may benefit from including alcohol-focused components designed to educate participants about the association between increased susceptibility to tobacco use when consuming alcohol and the role of alcohol in undermining tobacco cessation attempts.

Exposure to tobacco and e-cigarette advertisements by sexual identity status among high school students

INTRODUCTION

The literature on tobacco advertising among sexual minorities is relatively scarce. This study examined the association between exposure to tobacco products and e-cigarettes advertisements and sexual identity.

METHODS

Data were from the 2020 National Youth Tobacco Survey (n = 7223). The prevalence of exposure to tobacco marketing through various channels was estimated among high school students and by sexual identity subgroups. Multivariable logistic regressions were used to examine the association between sexual identity status and exposure to tobacco and e-cigarette advertisements.

RESULTS

The proportion of sexual minority adolescents who reported exposure to tobacco and e-cigarette advertisements was higher than heterosexuals. In multivariable analysis, gay or lesbian youth (aOR 1.45, 95% CI, 1.04-2.02) had higher odds of any exposure to tobacco and e-cigarette advertisement than heterosexuals. Regarding the channel of advertisement exposure, sexual minorities were more likely to be exposed via newspapers/magazines for cigarettes or other tobacco products. Likewise, gay or lesbian youth and those not sure about their sexual identity had higher odds of exposure via newspapers/magazines for e-cigarettes. Analysis stratified by sex showed significant differences, with gay or lesbian males more likely to be exposed to any tobacco and e-cigarette advertisements via the internet, newspapers/magazines, and TV/streaming services. Males not sure about their sexual identity are more likely to be exposed to tobacco and e-cigarette advertisements via newspapers/magazines.

CONCLUSIONS

Overall, sexual minority adolescents had high exposure to tobacco products and e-cigarette advertisements, especially males. Prevention and intervention efforts targeting this population could help reduce the well-established tobacco use disparities.

Perception and assumptions of young waterpipe smokers in Mumbai, India

Background

Hookah smoking has been on raise all over the world, including India, especially among youngsters. There is growing evidence suggesting the high school children experimenting this form of tobacco.

Objective

The objective of this study was to investigate the characteristics, behavior, and perceptions related to hookah smoking among the hookah smokers in Mumbai.

Materials and Methods

A cross-sectional survey was conducted among 200 randomly selected young adults between the age group of 15-35 years in Mumbai who visited different dental clinics. The questionnaire was distributed as Google Forms online in the month of November and December 2019 and those who submitted completed responses were included in the study.

Results

Only 114 participants returned with the completed forms in the time period of 2 months. The results showed that the majority of participants were between 20 and 24 age, comprising 58% who were having the habit of hookah smoking. Among which 24% females, 76% males had history of hookah habit. Eight percent of males started smoking hookah from very young age. Males (29.89%) shared one hookah pot with four members. Forty percent of the participants stated that they are interested to smoke again because of hookah flavor.

Conclusion

Easy availability of newer forms of smoking at online markets could play a role in promoting the use of hookah among youngsters. Most products are being sold without any warnings, and there is no means to control the selling of the products to minors. Educational intervention is urgently needed to create awareness among youth about the harmful effects of hookah smoking.

Leading Topics in Twitter Discourse on JUUL and Puff Bar Products: Content Analysis

Background

In response to the recent government restrictions, flavored JUUL products, which are rechargeable closed-system electronic cigarettes (e-cigarettes), are no longer available for sale. However, disposable closed-system products such as the flavored Puff Bar e-cigarette continues to be available. If e-cigarette consumers simply switch between products during the current government restrictions limited to 1 type of product over another, then such restrictions would be less effective. A step forward in this line of research is to understand how the public discusses these products by examining discourse referencing both Puff Bar and JUUL in the same conversation. Twitter data provide ample opportunity to capture such early trends that could be used to help public health researchers stay abreast of the rapidly changing e-cigarette marketplace.

Objective

The goal of this study was to examine public discourse referencing both Puff Bar and JUUL products in the same conversation on Twitter.

Methods

We collected data from Twitter’s streaming application programming interface between July 16, 2019, and August 29, 2020, which included both “Puff Bar” and “JUUL” (n=2632). We then used an inductive approach to become familiar with the data and generate a codebook to identify common themes. Saturation was determined to be reached with 10 themes.

Results

Posts often mentioned flavors, dual use, design features, youth use, health risks, switching 1 product for the other, price, confusion over the differences between products, longevity of the products, and nicotine concentration.

Conclusions

On examining the public’s conversations about Puff Bar and JUUL products on Twitter, having described themes in posts, this study aimed to help the tobacco control community stay informed about 2 popular e-cigarette products with different device features, which can be potentially substituted for one another. Future health communication campaigns may consider targeting the health consequences of using multiple e-cigarette products or dual use to reduce exposure to high levels of nicotine among younger populations.

Topics of Nicotine-Related Discussions on Twitter: Infoveillance Study

BACKGROUND

Cultural trends in the United States, the nicotine consumer marketplace, and tobacco policies are changing.

OBJECTIVE

The goal of this study was to identify and describe nicotine-related topics of conversation authored by the public and social bots on Twitter, including any misinformation or misconceptions that health education campaigns could potentially correct.

METHODS

Twitter posts containing the term "nicotine" were obtained from September 30, 2018 to October 1, 2019. Methods were used to distinguish between posts from social bots and nonbots. Text classifiers were used to identify topics in posts (n=300,360).

RESULTS

Prevalent topics of posts included vaping, smoking, addiction, withdrawal, nicotine health risks, and quit nicotine, with mentions of going "cold turkey" and needing help in quitting. Cessation was a common topic, with mentions of quitting and stopping smoking. Social bots discussed unsubstantiated health claims including how hypnotherapy, acupuncture, magnets worn on the ears, and time spent in the sauna can help in smoking cessation.

CONCLUSIONS

Health education efforts are needed to correct unsubstantiated health claims on Twitter and ultimately direct individuals who want to quit smoking to evidence-based cessation strategies. Future interventions could be designed to follow these topics of discussions on Twitter and engage with members of the public about evidence-based cessation methods in near real time when people are contemplating cessation.

Twitter Surveillance at the Intersection of the Triangulum

INTRODUCTION

A holistic public health surveillance approach can help capture the public's tobacco and marijuana-related attitudes and behaviors. Using publicly available data from Twitter, this is one of the first studies to describe key topics of discussions related to each intersection (e-cigarette, combustible tobacco, and marijuana) of the Triangulum framework.

METHOD

Twitter posts (n=999,447) containing marijuana, e-cigarette and combustible tobacco terms were collected from January 1, 2018, to December 23, 2019. Posts to Twitter with co-occurring mentions of keywords associated with the Triangulum were defined as an intersection (e-cigarettes and combustible tobacco, combustible tobacco and marijuana, e-cigarettes and marijuana, and marijuana, e-cigarettes and combustible tobacco). Text classifiers and unsupervised machine learning was used to identify predominant topics in posts.

RESULTS

Product Features and Cartridges were commonly referenced at the intersection of e-cigarette and marijuana-related conversations. Blunts and Cigars and Drugs and Alcohol were commonly referenced at the intersection of combustible tobacco and marijuana-related discussions. Flavors and Health Risks were discussed at the intersection of e-cigarette and combustible-related conversations, while discussions about Illicit products and Health risks were key topics of discussion when e-cigarettes, combustible tobacco, and marijuana were referenced all together in a single post.

CONCLUSION

By examining intersections of marijuana and tobacco products, this study offers inputs for designing comprehensive FDA regulations including regulating product features associated with appeal, improving enforcement to curb sales of illicit products, and informing the FDA's product review and standards procedures for tobacco products that can be used with marijuana.

IMPLICATIONS

This study is the first to leverage the Triangulum framework and Twitter data to describe key topics of discussions at the intersection of e-cigarette, combustible tobacco, and marijuana. Real-time health communication interventions can identify Twitter users posting in the context of e-cigarettes, combustible tobacco, and marijuana by automated methods and deliver tailored messages. This study also demonstrates the utility of Twitter data for surveillance of complex and evolving health behaviors.

Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review

BACKGROUND

Modifiable risky health behaviors, such as tobacco use, excessive alcohol use, being overweight, lack of physical activity, and unhealthy eating habits, are some of the major factors for developing chronic health conditions. Social media platforms have become indispensable means of communication in the digital era. They provide an opportunity for individuals to express themselves, as well as share their health-related concerns with peers and health care providers, with respect to risky behaviors. Such peer interactions can be utilized as valuable data sources to better understand inter-and intrapersonal psychosocial mediators and the mechanisms of social influence that drive behavior change.

OBJECTIVE

The objective of this review is to summarize computational and quantitative techniques facilitating the analysis of data generated through peer interactions pertaining to risky health behaviors on social media platforms.

METHODS

We performed a systematic review of the literature in September 2020 by searching three databases-PubMed, Web of Science, and Scopus-using relevant keywords, such as "social media," "online health communities," "machine learning," "data mining," etc. The reporting of the studies was directed by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Two reviewers independently assessed the eligibility of studies based on the inclusion and exclusion criteria. We extracted the required information from the selected studies.

RESULTS

The initial search returned a total of 1554 studies, and after careful analysis of titles, abstracts, and full texts, a total of 64 studies were included in this review. We extracted the following key characteristics from all of the studies: social media platform used for conducting the study, risky health behavior studied, the number of posts analyzed, study focus, key methodological functions and tools used for data analysis, evaluation metrics used, and summary of the key findings. The most commonly used social media platform was Twitter, followed by Facebook, QuitNet, and Reddit. The most commonly studied risky health behavior was nicotine use, followed by drug or substance abuse and alcohol use. Various supervised and unsupervised machine learning approaches were used for analyzing textual data generated from online peer interactions. Few studies utilized deep learning methods for analyzing textual data as well as image or video data. Social network analysis was also performed, as reported in some studies.

CONCLUSIONS

Our review consolidates the methodological underpinnings for analyzing risky health behaviors and has enhanced our understanding of how social media can be leveraged for nuanced behavioral modeling and representation. The knowledge gained from our review can serve as a foundational component for the development of persuasive health communication and effective behavior modification technologies aimed at the individual and population levels.

Options for waterpipe product regulation: A systematic review on product characteristics that affect attractiveness, addictiveness and toxicity of waterpipe use

INTRODUCTION

Despite its known adverse effects on human health, waterpipe smoking is increasing in popularity worldwide. However, compared to cigarettes, regulation of waterpipe product smoking lags behind and presents unique challenges. In search for regulatory options, this systematic review analyzes 36 studies on the differential effects on human health of the waterpipe characteristics including smoking products, heating sources, device components, and packages.

METHODS

A systematic review was performed according to PRISMA guidelines, revealing 443 unique citations. After screening, 36 studies were included in the results. Research articles were selected to inform on differential effects caused by product characteristics on adverse health effects, attractiveness, addictiveness and prevalence of waterpipe use.

RESULTS

Flavors are the key aspect that defines attractiveness of waterpipe product smoking. All waterpipe products, with or without nicotine, produce toxicants in similar quantities as cigarettes. Heating sources for waterpipe tobacco include charcoals and electrical heating. Both heating sources increase toxicant emissions in different ways. Hoses and mouth tips are device components that are often shared in waterpipe smoking. Sharing influences attractiveness by enriching the social experience. At the same time, it influences the transfer of infectious diseases by bacteria and viruses from one smoker to another. Studies showed that more generic and less attractive packages with health warnings are effective in reducing the attractiveness of waterpipe smoking.

CONCLUSIONS

Based on our findings, we advise to include all waterpipe products, tobacco and non-tobacco, with or without nicotine, in tobacco product regulations and smoking bans in order to: ban waterpipe molasses with characterizing flavors or ban the use of flavorings at any level; mandate dissemination of information on all waterpipe tobacco elements to the national regulator; prescribe testing to regulate contents of waterpipe smoking products and heating sources. Moreover, we advise to stimulate research on emissions of waterpipes.

The Potential of Smartphone Apps in Informing Protobacco and Antitobacco Messaging Efforts Among Underserved Communities: Longitudinal Observational Study

Background

People from underserved communities such as those from lower socioeconomic positions or racial and ethnic minority groups are often disproportionately targeted by the tobacco industry, through the relatively high levels of tobacco retail outlets (TROs) located in their neighborhood or protobacco marketing and promotional strategies. It is difficult to capture the smoking behaviors of individuals in actual locations as well as the extent of exposure to tobacco promotional efforts. With the high ownership of smartphones in the United States—when used alongside data sources on TRO locations—apps could potentially improve tobacco control efforts. Health apps could be used to assess individual-level exposure to tobacco marketing, particularly in relation to the locations of TROs as well as locations where they were most likely to smoke. To date, it remains unclear how health apps could be used practically by health promotion organizations to better reach underserved communities in their tobacco control efforts.

Objective

This study aimed to demonstrate how smartphone apps could augment existing data on locations of TROs within underserved communities in Massachusetts and Texas to help inform tobacco control efforts.

Methods

Data for this study were collected from 2 sources: (1) geolocations of TROs from the North American Industry Classification System 2016 and (2) 95 participants (aged 18 to 34 years) from underserved communities who resided in Massachusetts and Texas and took part in an 8-week study using location tracking on their smartphones. We analyzed the data using spatial autocorrelation, optimized hot spot analysis, and fitted power-law distribution to identify the TROs that attracted the most human traffic using mobility data.

Results

Participants reported encountering protobacco messages mostly from store signs and displays and antitobacco messages predominantly through television. In Massachusetts, clusters of TROs (Dorchester Center and Jamaica Plain) and reported smoking behaviors (Dorchester Center, Roxbury Crossing, Lawrence) were found in economically disadvantaged neighborhoods. Despite the widespread distribution of TROs throughout the communities, participants overwhelmingly visited a relatively small number of TROs in Roxbury and Methuen. In Texas, clusters of TROs (Spring, Jersey Village, Bunker Hill Village, Sugar Land, and Missouri City) were found primarily in Houston, whereas clusters of reported smoking behaviors were concentrated in West University Place, Aldine, Jersey Village, Spring, and Baytown.

Conclusions

Smartphone apps could be used to pair geolocation data with self-reported smoking behavior in order to gain a better understanding of how tobacco product marketing and promotion influence smoking behavior within vulnerable communities. Public health officials could take advantage of smartphone data collection capabilities to implement targeted tobacco control efforts in these strategic locations to reach underserved communities in their built environment.

Infodemiology and Infoveillance: Scoping Review

Background

Web-based sources are increasingly employed in the analysis, detection, and forecasting of diseases and epidemics, and in predicting human behavior toward several health topics. This use of the internet has come to be known as infodemiology, a concept introduced by Gunther Eysenbach. Infodemiology and infoveillance studies use web-based data and have become an integral part of health informatics research over the past decade.

Objective

The aim of this paper is to provide a scoping review of the state-of-the-art in infodemiology along with the background and history of the concept, to identify sources and health categories and topics, to elaborate on the validity of the employed methods, and to discuss the gaps identified in current research.

Methods

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to extract the publications that fall under the umbrella of infodemiology and infoveillance from the JMIR, PubMed, and Scopus databases. A total of 338 documents were extracted for assessment.

Results

Of the 338 studies, the vast majority (n=282, 83.4%) were published with JMIR Publications. The Journal of Medical Internet Research features almost half of the publications (n=168, 49.7%), and JMIR Public Health and Surveillance has more than one-fifth of the examined studies (n=74, 21.9%). The interest in the subject has been increasing every year, with 2018 featuring more than one-fourth of the total publications (n=89, 26.3%), and the publications in 2017 and 2018 combined accounted for more than half (n=171, 50.6%) of the total number of publications in the last decade. The most popular source was Twitter with 45.0% (n=152), followed by Google with 24.6% (n=83), websites and platforms with 13.9% (n=47), blogs and forums with 10.1% (n=34), Facebook with 8.9% (n=30), and other search engines with 5.6% (n=19). As for the subjects examined, conditions and diseases with 17.2% (n=58) and epidemics and outbreaks with 15.7% (n=53) were the most popular categories identified in this review, followed by health care (n=39, 11.5%), drugs (n=40, 10.4%), and smoking and alcohol (n=29, 8.6%).

Conclusions

The field of infodemiology is becoming increasingly popular, employing innovative methods and approaches for health assessment. The use of web-based sources, which provide us with information that would not be accessible otherwise and tackles the issues arising from the time-consuming traditional methods, shows that infodemiology plays an important role in health informatics research.

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study (Preprint).. [DOI: 10.2196/preprints.19016]

BACKGROUND

The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world’s health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately.

OBJECTIVE

This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic.

METHODS

Leveraging a set of tools (Twitter’s search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms (“corona,” “2019-nCov,” and “COVID-19”), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic.

RESULTS

Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings).

CONCLUSIONS

Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.

Cannabis Surveillance With Twitter Data: Emerging Topics and Social Bots

Objectives. To use publicly accessible data from people who post to Twitter to rapidly capture and describe the public's recent experiences with cannabis.Methods. We obtained Twitter posts containing cannabis-related terms from May 1, 2018, to December 31, 2018. We used methods to distinguish between posts from social bots and nonbots. We used text classifiers to identify topics in posts (n = 60 861).Results. Prevalent topics of posts included using cannabis with mentions of cannabis initiation, processed cannabis products, and health and medical with posts suggesting that cannabis could help with cancer, sleep, pain, anxiety, depression, trauma, and posttraumatic stress disorder. Polysubstance use was a common topic with mentions of cocaine, heroin, ecstasy, LSD, meth, mushrooms, and Xanax along with cannabis. Social bots regularly made health claims about cannabis.Conclusions. Findings suggest that processed cannabis products, unsubstantiated health claims about cannabis products, and the co-use of cannabis with legal and illicit substances warrant considerations by public health researchers in the future.

E-liquid-related posts to Twitter in 2018: Thematic analysis

INTRODUCTION

E-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and communicative cues associated with e-liquids. We analyzed Twitter data to characterize key topics of conversation about e-liquids to inform surveillance, and regulatory efforts.

METHODS

Twitter posts containing e-liquid-related terms ("e-liquid(s)," "e-juice(s)") were obtained from 1 January 2018 to 31 December 2018. Text classifiers were used to identify topics of the posts (n = 15,927).

RESULTS

The most prevalent topic was Promotional at 29.35% followed by Flavors at 24.22%, and Person Tagging at 21.47%. Juice Composition was next most prevalent at 17.61% followed by Cannabis at 16.83%, and Nicotine Health Risks at 6.39%. Quit Smoking was rare at 0.57%.

CONCLUSION

These results suggest that flavors, cannabis, health risks of nicotine, and composition warrant consideration as targets in future surveillance, public policy, and interventions addressing the use of e-liquids. Twitter provides ample opportunity to influence the normalization, and uptake, of e-cigarette-related products among non-smokers and youth, unless regulatory restrictions, and counter messaging campaigns are developed to reduce this risk.

The effects of hookah/waterpipe smoking on general health and the cardiovascular system

Hookah or waterpipe smoking or use is an emerging trend in the US population, especially among the youth. The misperception of hookah being less harmful than cigarettes and the availability of different but "appealing" flavors are considered among the main reasons for this trend. Hookah users however are exposed to many of the same toxic compounds/by-products as cigarette users, but at dramatically higher levels, which might lead to more severe negative health effects. In fact, hookah users are at risks of infections, cancers, lung disease, and other medical conditions. Moreover, because of the overlapping toxicant/chemical profile to conventional cigarettes, hookah smoke effects on the cardiovascular system are thought to be comparable to those of conventional cigarettes. A major source of tobacco addiction is nicotine, whose levels in hookah are extremely variable as they depend on the type of tobacco used. Taken together, in this review of literature, we will provide insights on the negative health effects of hookah in general, with a focus on what is known regarding its impact on the cardiovascular system.

Characterizing Swisher Little Cigar-Related Posts on Twitter in 2018: Text Analysis

Background

Little cigars are growing in popularity in the United States, and Swisher is the market leader. The contexts and experiences associated with the use of Swisher-related products is understudied, but such information is available via publicly available posts on Twitter.

Objective

This study aimed to analyze Twitter posts to characterize Twitter users’ recent experiences with Swisher-related products.

Methods

Twitter posts containing the term “swisher” were analyzed from January 1, 2018, to December 31, 2018. Text classifiers were used to identify topics in posts (n=81,333).

Results

The most prevalent topic was Person Tagging (mentioning a Twitter account in a post; 32.77%), followed by Flavors (eg, Grape and Strawberry; 20.96%) and Swisher use (eg, smoke swisher; 17.44%). Additional topics included Cannabis use (eg, blunt, roll, and gut swisher; 6.26%), Appeal (eg, like Swisher; 5.92%), Dislike (eg, posts that showed dissatisfaction with Swisher products; 3.53%), Purchases (eg, buy swisher; 1.90%), and Cigar comparison (eg, mentions of other cigar products including White-owl and Backwoods; 1.64%).

Conclusions

This paper describes common contexts and experiences associated with the use of Swisher little cigars from the population posting on Twitter in 2018. These online messages may have offline consequences for tobacco-related behaviors, indicating the need for countering from public health officials. Findings should inform us about targets for surveillance, policy, and interventions addressing Swisher little cigars as well as communication planning and tobacco product counter messaging on Twitter.

Google Trends in Infodemiology and Infoveillance: Methodology Framework

Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest in selected keywords and topics over time. Online search traffic data from Google have been shown to be useful in analyzing human behavior toward health topics and in predicting disease occurrence and outbreaks. Despite the large number of Google Trends studies during the last decade, the literature on the subject lacks a specific methodology framework. This article aims at providing an overview of the tool and data and at presenting the first methodology framework in using Google Trends in infodemiology and infoveillance, including the main factors that need to be taken into account for a strong methodology base. We provide a step-by-step guide for the methodology that needs to be followed when using Google Trends and the essential aspects required for valid results in this line of research. At first, an overview of the tool and the data are presented, followed by an analysis of the key methodological points for ensuring the validity of the results, which include selecting the appropriate keyword(s), region(s), period, and category. Overall, this article presents and analyzes the key points that need to be considered to achieve a strong methodological basis for using Google Trends data, which is crucial for ensuring the value and validity of the results, as the analysis of online queries is extensively integrated in health research in the big data era.