Identifying Topics for E-Cigarette User-Generated Contents: A Case Study From Multiple Social Media Platforms

Differentiating the associations of passive and active social media use with e-cigarette use among U.S. youth

PURPOSE

The impacts of passive (i.e., browsing) versus active (i.e., engagement) use of social media on e-cigarette use among youth have been understudied in existing literature. This study examines how passive and active use of social media are differentially associated with e-cigarette use among youth and how risk perceptions mediate these associations.

METHODS

Pooled data from the 2021 and 2022 National Youth Tobacco Survey (N=48,704, aged 11-19) were used. Weighted structural equation models were employed to estimate the associations between passive and active social media use and youth e-cigarette use.

RESULTS

Both passive and active social media use were associated with higher odds and more days of e-cigarette use among youth. E-cigarette risk perceptions mediated the associations between active use and both the likelihood of ever using e-cigarettes and the number of days of use. Risk perceptions mediated the association between active, but not passive, use and the number of days of e-cigarette use. Compared to passive use, active use was overall associated with higher odds and more days of youth e-cigarette use.

DISCUSSION

The findings suggest that public health efforts should distinguish between passive and active social media use when designing and executing interventions. Attention and efforts should also be directed towards understanding the distinct indirect effects of passive and active social media use through risk perceptions. These findings advance our theoretical understanding of the role of different types of social media use and offer significant practical insights for interventions.

Exposure to user-generated e-cigarette content on social media associated with greater vulnerability to e-cigarette use among youth non-users

INTRODUCTION

Social media are important venues for youth's exposure to e-cigarette content. This study examined how exposure to user-generated e-cigarette content (i.e., content created and shared by individual social media users) is associated with vulnerabilities to e-cigarette use among youth non-users.

METHODS

We pooled data from the 2021 and 2022 National Youth Tobacco Survey. Youth who have never used e-cigarettes were included. Weighted linear and logistic regressions were conducted to examine how exposure to user-generated e-cigarette content (from real-life friends, online-only friends, and celebrities/influencers) on social media was associated with e-cigarette use vulnerabilities measured by perceived norms, perceived risk, and susceptibility of use, controlling for demographics, advertising exposure, and mental health conditions. Multiple imputations were performed to account for missing data.

RESULTS

Exposure to e-cigarette content on social media posted by real-life friends, online-only friends, and celebrities/influencers were associated with more positive descriptive norm (βs = 1.56, 0.37, and 0.35, respectively, all ps < .001), more positive injunctive norm (βs = 0.46, 0.19, and 0.10, respectively, all ps < .001), and higher odds of e-cigarette use susceptibility (ORs = 1.48, 1.50. 1.29, respectively, all ps < .001). Exposure to content posted by real-life and online-only friends were associated with reduced risk perception of e-cigarette use (β = -0.04, p < 0.05 and β = -0.07, p < 0.001).

CONCLUSIONS

Our study highlighted that friends and celebrities/influencers are important sources on social media that can influence youth non-users' vulnerabilities to e-cigarette use. Interventional messages communicated through friends and influencers on social media may in turn help reduce e-cigarette vulnerability among youth non-users.

Relationship Between Product Features and the Prices of e-Cigarette Devices Sold in Web-Based Vape Shops: Comparison Study Using a Linear Regression Model

BACKGROUND

Open-system electronic cigarette (EC) product features, such as battery capacity, maximum output wattage, and so forth, are major components that drive product costs and may influence use patterns. Moreover, continued innovation and monitoring of product features and prices will provide critical information for designing appropriate taxation policies and product regulations.

OBJECTIVE

This study will examine how product features are associated with the prices of devices sold in web-based vape shops.

METHODS

We draw samples from 5 popular, US-based, web-based vape shops from April to August 2022 to examine starter kits, device-only products, and e-liquid container-only products. We implemented a linear regression model with a store-fixed effect to examine the association between device attributes and prices.

RESULTS

EC starter kits or devices vary significantly by type, with mod prices being much higher than pod and vape pen prices. The prices of mod starter kits were even lower than those of mod devices, suggesting that mod starter kits are discounted in web-based vape shops. The price of mod kits, mod device-only products, and pod kits increased as the battery capacity and output wattage increased. For vape pens, the price was positively associated with the volume size of the e-liquid container. On the other hand, the price of pod kits was positively associated with the number of containers.

CONCLUSIONS

A unit-based specific tax, therefore, will impose a higher tax burden on lower-priced devices such as vape pens or pod systems and a lower tax burden on mod devices. A volume- or capacity-based specific tax on devices will impose a higher tax burden on vape pens with a larger container size. Meanwhile, ad valorem taxes pegged to wholesale or retail prices would apply evenly across device types, meaning those with advanced features such as higher battery capacities and output wattage would face higher rates. Therefore, policy makers could manipulate tax rates by device type to discourage the use of certain device products.

Multiple-Perspective Data-Driven Analysis of Online Health Communities

The growth of online health communities and socially generated health-related content has the potential to provide considerable value for patients and healthcare providers alike. For example, members of the public can acquire medical knowledge and interact with others online. However, the volume of information-and the consequent 'noise' associated with large data volumes-can create difficulties for users. In this paper, we present a data-driven approach to better understand these data from multiple stakeholder perspectives. We utilise three techniques-sentiment analysis, content analysis, and topic analysis-to analyse user-generated medical content related to Lyme disease. We use a supervised feature-based model to identify sentiments, content analysis to identify concepts that predominate, and latent Dirichlet allocation strategy as an unsupervised generative model to identify topics represented in the discourse. We validate that applying three different analytic methods highlights differing aspects of the information different stakeholders will be interested in based on the goals of different stakeholders, expert opinion, and comparison with patient information leaflets.

Social Media Use and Subsequent E-Cigarette Susceptibility, Initiation, and Continued Use Among US Adolescents

INTRODUCTION

Social media has a large amount of e-cigarette content. Little is known about the associations between social media use and a wide range of e-cigarette use behaviors, including susceptibility, initiation, and continued use. We analyzed national data on US adolescents to assess these associations.

METHODS

We used data on adolescents participating in the Population Assessment of Tobacco and Health (PATH) Study Wave 4 (2016-2018) and Wave 5 (2018-2019). We conducted 2 models: 1) a multinomial logistic regression on e-cigarette use susceptibility and use behaviors at Wave 5 by social media use at Wave 4 among adolescents who never used e-cigarettes at Wave 4 and 2) a binomial logistic regression on current e-cigarette use at Wave 5 by social media use at Wave 4 among adolescents who ever used e-cigarettes at Wave 4.

RESULTS

Among adolescents who never used e-cigarettes at Wave 4 (n = 7,872), daily social media use (vs never) was associated with a higher likelihood of being susceptible to e-cigarette use (adjusted odds ratio [aOR] =1.46; 95% CI, 1.20-1.78), past e-cigarette use (aOR = 3.55; 95% CI, 2.49-5.06), and current e-cigarette use (aOR = 3.45; 95% CI, 2.38-5.02) at Wave 5. Among adolescents who ever used e-cigarettes at Wave 4 (n = 794), we found no significant association between social media use at Wave 4 and continued e-cigarette use at Wave 5.

CONCLUSION

Our study found that social media use is associated with subsequent susceptibility to e-cigarette use and initiation but not with continued use of e-cigarettes among US adolescents. These findings suggest that understanding and addressing the association between social media and e-cigarette use is critical.

How Attitude and Para-Social Interaction Influence Purchase Intentions of Mukbang Users: A Mixed-Method Study

Mukbang is widely recognized as a new type of food video on user-generated content (UGC) platforms. The purpose of this study was to identify motivators to watch mukbangs and to examine the relationship between these motivators and the intention to watch mukbangs via attitudes toward mukbangs and para-social relationships. In addition, this study examined how the intention to watch mukbangs affected purchase intention. Interviews were conducted to determine the motivation factors for watching mukbangs by collecting data from mukbang viewers. The results of the interviews suggested that vicarious satisfaction, enjoyment, information, exposure, and attractiveness were motivators for watching mukbangs. Using a survey, this study collected data from 399 participants who watched mukbangs to test relationships. Using SmartPLS, structural equation modeling (SEM) was conducted. The outcomes of the SEM indicated that vicarious satisfaction, enjoyment, and information influenced the intention to watch mukbangs via attitudes toward mukbangs. The results also indicated that exposure and attractiveness had an impact on the intention to watch mukbangs via para-social relationships. Furthermore, the intention to watch mukbangs influenced the intention to purchase food items portrayed in the mukbang content. This study contributes to the literature by empirically confirming the effect of watching mukbang on purchase intention.

"They're sleek, stylish and sexy:" selling e-cigarettes online

OBJECTIVE

We examined the product range, marketing strategies, access and marketing claims made by Australian and New Zealand (NZ) online e-cigarette retailers.

METHODS

Twenty Australian (n=10) and NZ (n=10) e-cigarette retail websites were identified via Google using a combination of keywords nominated by an expert panel and identified via a literature review: 'e-cigarette', 'e-cigs', 'vape', and 'vaping', combined with 'Australia', 'AU', 'New Zealand' and 'NZ' and then examined.

RESULTS

Products were extensive (disposable, pod-based, reusable, replacement parts), 95% (n=19) offered 'Starter Kits,' flavoured e-liquid (n=1,032), most containing nicotine (70%, n=14). Most retailers (85%, n=17) offered price discounts and free delivery. There were unsubstantiated health claims (80%, n=16), cessation claims (65%, n=13) and cost-benefit claims (50%, n=10) promoting e-cigarette use. Most (n=14) website age verification features simply required the purchaser to indicate they were aged 18 years.

CONCLUSIONS

Although e-cigarette regulations are different in Australia and NZ, the online product range, marketing strategies, access and marketing claims were similar and sold e-liquid containing nicotine. The health and cessation e-cigarette marketing claims were outlandish and unsubstantiated.

IMPLICATIONS FOR PUBLIC HEALTH

Most purchasing of e-cigarettes occurs online. Regulations and enforcement to limit access and stop unsubstantiated marketing claims must be a public health priority.

Describing Memes Referencing Vaping: Thematic Analysis

Background: Memes, images or videos with text overlay that embody a concept or belief about the contemporary society, are endemic to Internet culture, are popular among youth and diffuse rapidly across social media platforms. E-cigarettes and vaping have grown in popularity in the era of Internet culture however there is little research describing the intersection of memes and vaping. This is an important gap in the literature as memes may be part of the broader online e-cigarette information landscape that can normalize vaping among young people. Memes could also point to emerging trends in product preferences. This study content analyzed memes to identify key themes, characters and vape products depicted therein. Methods: Data were drawn from a sub-reddit devoted to vaping-related memes. Memes were electronically copied from the forum to analyze (n = 527). Using an inductive approach, the research team identified 14 themes. Results: In-group communication (n = 202, 38.33%) was the most predominant theme followed by Critique of vaping regulations and public perceptions (n = 76, 14.42%), and Vape device modifications and hacks (n = 62, 11.76%). Memes included Cartoons (n = 124, 23.53%), Celebrities (n = 75, 14.23%), and Fictional characters (n = 53, 10.06%). Memes referenced Tanks or mods (n = 120, 22.77%), Component parts (n = 96, 18.22%) and E-liquids/Nicotine salts (n = 81, 15.37%). Conclusion: Memes referenced in-group communication and cartoons among other youth friendly images, raising concern about the potential to normalize vaping-related behaviors. Future research should monitor emerging vape devices and determine the impact of memes on attitudes and behaviors among adolescents and young adults. Implications: Given the popularity and reach of memes among youth, continuous monitoring of vaping-related memes may reveal aspects that may be addressed in vaping prevention campaigns.

Expanding the E-Liquid Flavor Wheel: Classification of Emerging E-Liquid Flavors in Online Vape Shops

INTRODUCTION

Electronic cigarettes are the most popular tobacco product among U.S. youth, and over 80% of current youth users of e-cigarettes use flavored e-cigarettes, with fruit, mint/menthol, and candy/sweets being the most popular flavors. A number of new e-liquid flavors are currently emerging in the online e-cigarette market. Menthol and other flavored e-cigarettes could incentivize combustible tobacco smokers to transition to e-cigarette use.

METHODS

From February to May 2021, we scraped data of over 14,000 e-liquid products, including detailed descriptions of their flavors, from five national online vape shops. Building upon the existing e-liquid flavor wheel, we expanded the semantic databases (i.e., key terms) to identify flavors using WordNet-a major database for keyword matching and group discussion. Using the enriched databases, we classified 14,000+ e-liquid products into the following 11 main flavor categories: "fruit", "dessert/candy/sweets", "coffee/tea", "alcohol", "other beverages", "tobacco", "mint/menthol", "nuts", "spices/pepper", "other flavors", and "unspecified flavor".

RESULTS

We find that the most prominent flavor sold in the five online vape shop in 2021 was fruit flavored products, followed by dessert/candy/other sweets. Online vendors often label a product with several flavor profiles, such as fruit and menthol.

CONCLUSIONS

Given that online stores market products with multiple flavor profiles and most of their products contain fruit flavor, the FDA may have issued marketing denial orders to some of these products. It is important to further examine how online stores respond to the FDA flavor restrictions (e.g., compliance or non-compliance).

Implicit Incentives Among Reddit Users to Prioritize Attention Over Privacy and Reveal Their Faces When Discussing Direct-to-Consumer Genetic Test Results: Topic and Attention Analysis

Background

As direct-to-consumer genetic testing services have grown in popularity, the public has increasingly relied upon online forums to discuss and share their test results. Initially, users did so anonymously, but more recently, they have included face images when discussing their results. Various studies have shown that sharing images on social media tends to elicit more replies. However, users who do this forgo their privacy. When these images truthfully represent a user, they have the potential to disclose that user's identity.

Objective

This study investigates the face image sharing behavior of direct-to-consumer genetic testing users in an online environment to determine if there exists an association between face image sharing and the attention received from other users.

Methods

This study focused on r/23andme, a subreddit dedicated to discussing direct-to-consumer genetic testing results and their implications. We applied natural language processing to infer the themes associated with posts that included a face image. We applied a regression analysis to characterize the association between the attention that a post received, in terms of the number of comments, the karma score (defined as the number of upvotes minus the number of downvotes), and whether the post contained a face image.

Results

We collected over 15,000 posts from the r/23andme subreddit, published between 2012 and 2020. Face image posting began in late 2019 and grew rapidly, with over 800 individuals revealing their faces by early 2020. The topics in posts including a face were primarily about sharing, discussing ancestry composition, or sharing family reunion photos with relatives discovered via direct-to-consumer genetic testing. On average, posts including a face image received 60% (5/8) more comments and had karma scores 2.4 times higher than other posts.

Conclusions

Direct-to-consumer genetic testing consumers in the r/23andme subreddit are increasingly posting face images and testing reports on social platforms. The association between face image posting and a greater level of attention suggests that people are forgoing their privacy in exchange for attention from others. To mitigate this risk, platform organizers and moderators could inform users about the risk of posting face images in a direct, explicit manner to make it clear that their privacy may be compromised if personal images are shared.

A thematic cluster analysis of parents' online discussions about fussy eating

Food fussiness is associated with non‐responsive parent feeding practices, such as persuasive and instrumental feeding. Although most children described as ‘fussy eaters’ are likely exhibiting developmentally typical behaviours, up to half of the parents of children 2–5 years old express concerns. Concern for fussy eating may mediate the use of non‐responsive feeding practices and so must be addressed in parent feeding interventions. Therefore, it is critical to better understand parents' concerns and how they may relate to feeding practices. This study aimed to explore how parents' feeding practices and the social cognitive factors that may drive them clustered based on parents' concern for fussy eating. Data were collected from parent discussions of fussy eating on a Reddit forum (80,366 posts). Latent Dirichlet allocation was used to identify discussions of fussy eating. Relevant posts (1542) made by users who identified as a parent of a fussy eater (n = 630) underwent qualitative coding and thematic analysis. Five clusters of parents were identified, ranging in size from 53 to 189 users. These were primarily characterised by parents' degree of concern and feeding practices: (1) High concern, nonresponsive; (2) Concerned, nonresponsive; (3) Low concern, responsive; (4) Low concern, mixed strategies; (5) Low concern, indulgent. Parents who used responsive practices tended to be less concerned for fussy eating, have greater trust in their child's ability to self‐regulate hunger, have longer‐term feeding goals, and exhibit greater ability for personal self‐regulation. Future research should further examine how these constructs may be leveraged in parent feeding interventions.

Parents using nonresponsive practices to manage fussy eating may have more concerns about fussy eating, less trust in their child's ability to self‐regulate hunger, shorter‐term feeding goals, and less developed self‐regulation skills.

As most children described as “fussy eaters” are likely exhibiting developmentally typical behaviours, interventions addressing nutrition and feeding practices in early childhood should aim to alleviate parental concern for fussy eating, for example, by helping them recognise developmentally normal eating behaviours.

Early childhood feeding interventions may also be enhanced by helping parents to develop long‐term feeding goals and improved self‐regulation skills in the context of their feeding practices.

Understanding Public Perceptions of Per- and Polyfluoroalkyl Substances: Infodemiology Study of Social Media

Background

Per- and polyfluoroalkyl substances (PFAS) are environmental contaminants that have received significant public attention. PFAS are a large group of human-made chemicals that have been used in industry and consumer products worldwide since the 1950s. Human exposure to PFAS is a growing public health concern. Studies suggest that exposure to PFAS may increase the risk of some cancers and have negative health impacts on the endocrine, metabolic, and immune systems. Federal and state health partners are investigating the exposure to and possible health effects associated with PFAS. Government agencies can observe social media discourse on PFAS to better understand public concerns and develop targeted communication and outreach efforts.

Objective

The primary objective of this study is to understand how social media is used to share, disseminate, and engage in public discussions of PFAS-related information in the United States.

Methods

We investigated PFAS-related content across 2 social media platforms between May 1, 2017, and April 30, 2019, to identify how social media is used in the United States to seek and disseminate PFAS-related information. Our key variable of interest was posts that mentioned “PFAS,” “PFOA,” “PFOS,” and their hashtag variations across social media platforms. Additional variables included post type, time, PFAS event, and geographic location. We examined term use and post type differences across platforms. We used descriptive statistics and regression analysis to assess the incidence of PFAS discussions and to identify the date, event, and geographic patterns. We qualitatively analyzed social media content to determine the most prevalent themes discussed on social media platforms.

Results

Our analysis revealed that Twitter had a significantly greater volume of PFAS-related posts compared with Reddit (98,264 vs 3126 posts). PFAS-related social media posts increased by 670% over 2 years, indicating a marked increase in social media users’ interest in and awareness of PFAS. Active engagement varied across platforms, with Reddit posts demonstrating more in-depth discussions compared with passive likes and reposts among Twitter users. Spikes in PFAS discussions were evident and connected to the discovery of contamination events, media coverage, and scientific publications. Thematic analysis revealed that social media users see PFAS as a significant public health concern and seek a trusted source of information about PFAS-related public health efforts.

Conclusions

The analysis identified a prevalent theme—on social media, PFAS are perceived as an immediate public health concern, which demonstrates a growing sense of urgency to understand this emerging contaminant and its potential health impacts. Government agencies can continue using social media research to better understand the changing community sentiment on PFAS and disseminate targeted information and then use social media as a forum for dispelling misinformation, communicating scientific findings, and providing resources for relevant public health services.

The Public Perception of the #GeneEditedBabies Event Across Multiple Social Media Platforms: Observational Study

Background

In November 2018, a Chinese researcher reported that his team had applied clustered regularly interspaced palindromic repeats or associated protein 9 to delete the gene C-C chemokine receptor type 5 from embryos and claimed that the 2 newborns would have lifetime immunity from HIV infection, an event referred to as #GeneEditedBabies on social media platforms. Although this event stirred a worldwide debate on ethical and legal issues regarding clinical trials with embryonic gene sequences, the focus has mainly been on academics and professionals. However, how the public, especially stratified by geographic region and culture, reacted to these issues is not yet well-understood.

Objective

The aim of this study is to examine web-based posts about the #GeneEditedBabies event and characterize and compare the public’s stance across social media platforms with different user bases.

Methods

We used a set of relevant keywords to search for web-based posts in 4 worldwide or regional mainstream social media platforms: Sina Weibo (China), Twitter, Reddit, and YouTube. We applied structural topic modeling to analyze the main discussed topics and their temporal trends. On the basis of the topics we found, we designed an annotation codebook to label 2000 randomly sampled posts from each platform on whether a supporting, opposing, or neutral stance toward this event was expressed and what the major considerations of those posts were if a stance was described. The annotated data were used to compare stances and the language used across the 4 web-based platforms.

Results

We collected >220,000 posts published by approximately 130,000 users regarding the #GeneEditedBabies event. Our results indicated that users discussed a wide range of topics, some of which had clear temporal trends. Our results further showed that although almost all experts opposed this event, many web-based posts supported this event. In particular, Twitter exhibited the largest number of posts in opposition (701/816, 85.9%), followed by Sina Weibo (968/1140, 84.91%), Reddit (550/898, 61.2%), and YouTube (567/1078, 52.6%). The primary opposing reason was rooted in ethical concerns, whereas the primary supporting reason was based on the expectation that such technology could prevent the occurrence of diseases in the future. Posts from these 4 platforms had different language uses and patterns when they expressed stances on the #GeneEditedBabies event.

Conclusions

This research provides evidence that posts on web-based platforms can offer insights into the public’s stance on gene editing techniques. However, these stances vary across web-based platforms and often differ from those raised by academics and policy makers.

#NicotineAddictionCheck: Puff Bar Culture, Addiction Apathy, and Promotion of E-Cigarettes on TikTok

This study aimed to classify and delineate types of user-generated content about the disposable e-cigarette Puff Bar shared on the popular video-based social media platform TikTok. We qualitatively analyzed 148 popular TikTok videos collected in July 2020. During an iterative process of data reduction and thematic analysis, we categorized videos by overarching genres and identified emergent themes. Young adults were engaged at all stages of the research process. Together, videos were viewed over 137 million times on TikTok. Seven genres of Puff Bar content emerged: skits and stories, shared vaper experiences, videos to show off, product reviews, product unboxing, promotion of Puff Bar, and crafts. Videos depicted Puff Bar users’ apathy about addiction and a lack of concern of the health effects of e-cigarette use. Additionally, Puff Bar promotion content from underground retailers was extensive and some targeted underage persons. Qualitative analysis of social media content can richly describe emerging online culture and illuminate the motivations of adolescent and young adult e-cigarette use. Social media can facilitate new product adoption; comprehensive e-cigarette regulation and enforcement can counteract these effects by closing loopholes through which new products emerge.

E-cigarettes use among university students in Jordan: Perception and related knowledge

The use of e-cigarettes has been increasing in popularity among people, especially young adults. Assessing young individuals’ perceptions of e-cigarettes can help to identify factors that may influence their decision to use e-cigarettes. To examine prevalence, perceptions, and knowledge of e-cigarettes among university students in Jordan, an observational cross-sectional study using an online self-administered questionnaire was conducted among students from public and private universities between October 2020 and January 2021. A total of 1259 university students completed the questionnaire. Approximately, 11% of participants reported e-cigarettes use. Among users, 26.5% used it for the purpose of smoking cessation, while 22% of them used it out of curiosity, and 20.5% used it as they believed it is less harmful than other tobacco products. Multivariate analysis showed that conventional cigarette smokers were independently associated with a better knowledge about e-cigarettes (OR = 1.496, 95CI% = 1.018–2.197, p-value = 0.040). In addition, medical students showed a significantly better knowledge compared to non-medical students (OR = 1.710, 95CI% = 1.326–2.204, p-value = <0.001). In Jordan, e-cigarettes use is less popular compared to other countries. Nonetheless, educational interventions are needed to correct misconceptions about e-cigarettes among young adults.

Emotional Responses and Perceived Relative Harm Mediate the Effect of Exposure to Misinformation about E-Cigarettes on Twitter and Intention to Purchase E-Cigarettes among Adult Smokers

There is a gap in knowledge on the affective mechanisms underlying effects of exposure to health misinformation. This study aimed to understand whether discrete emotional responses and perceived relative harm of e-cigarettes versus smoking mediate the effect of exposure to tweets about the harms of e-cigarettes on Twitter and intention to purchase e-cigarettes among adult smokers. We conducted a web-based experiment in November 2019 among 2400 adult smokers who were randomly assigned to view one of four conditions of tweets containing different levels of misinformation. We fitted mediation models using structural equation modeling and bootstrap procedures to assess the indirect effects of exposure to tweets through perceived relative harm of e-cigarettes and six discrete emotions. Our findings support that exposure to tweets about harms of e-cigarettes influence intention to purchase e-cigarettes through perceived relative harm, discrete emotional responses, and serially through emotional responses and perceived relative harm. Feeling worried, hopeful, and happy mediated the effects of condition on intention to purchase e-cigarettes. Feeling scared, worried, angry, and hopeful mediated the effects serially through perceived relative harm. Affective responses and perceived relative harm following exposure to misinformation about e-cigarette harm may mediate the relationship with intention to purchase e-cigarettes among adult smokers.

Social media mining in drug development-Fundamentals and use cases

The incorporation of patients' perspectives into drug discovery and development has become critically important from the viewpoint of accounting for modern-day business dynamics. There is a trend among patients to narrate their disease experiences on social media. The insights gained by analyzing the data pertaining to such social-media posts could be leveraged to support patient-centered drug development. Manual analysis of these data is nearly impossible, but artificial intelligence enables automated and cost-effective processing, also referred as social media mining (SMM). This paper discusses the fundamental SMM methods along with several relevant drug-development use cases.

Categorising patient concerns using natural language processing techniques

OBJECTIVES

Patient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis. This study reports the results of using a semiautomated, computational topic-modelling approach to analyse a corpus of patient feedback.

METHODS

Patient concerns were received by Alberta Health Services between 2011 and 2018 (n=76 163), regarding 806 care facilities in 163 municipalities, including hospitals, clinics, community care centres and retirement homes, in a province of 4.4 million. Their existing framework requires manual labelling of pre-defined categories. We applied an automated latent Dirichlet allocation (LDA)-based topic modelling algorithm to identify the topics present in these concerns, and thereby produce a framework-free categorisation.

RESULTS

The LDA model produced 40 topics which, following manual interpretation by researchers, were reduced to 28 coherent topics. The most frequent topics identified were communication issues causing delays (frequency: 10.58%), community care for elderly patients (8.82%), interactions with nurses (8.80%) and emergency department care (7.52%). Many patient concerns were categorised into multiple topics. Some were more specific versions of categories from the existing framework (eg, communication issues causing delays), while others were novel (eg, smoking in inappropriate settings).

DISCUSSION

LDA-generated topics were more nuanced than the manually labelled categories. For example, LDA found that concerns with community care were related to concerns about nursing for seniors, providing opportunities for insight and action.

CONCLUSION

Our findings outline the range of concerns patients share in a large health system and demonstrate the usefulness of using LDA to identify categories of patient concerns.

Categorizing IQOS-Related Twitter Discussions

(1) Background: The heated tobacco product IQOS, by Philip Morris International, is now available in over 55 countries, including the United States. Social media sites such as Twitter are often used to promote or discuss tobacco products, though prior research has not examined how IQOS is presented on Twitter. (2) Methods: This study collected and categorized Twitter conversations involving IQOS. A manual content analysis was performed on N = 3916 English tweets related to IQOS published internationally between 1 January 2020 and 30 June 2020. (3) Results: Most tweets were either online marketing for IQOS (32.3%) or personal testimonials related to IQOS use (34.2%). Personal testimonial tweets made harm reduction claims about IQOS either as an avenue to quit smoking/tobacco use (3.4%), or in comparison to combustible cigarettes (2.0%). Tobacco policy-related tweets were detected (13.9%), split between discussions of United States (4.9%) and international (4.4%) policies. News media tweets (14.2%) were also detected. (4) Conclusions: Our study suggests IQOS may be understood as a less harmful alternative to vaping and combustible cigarettes. Discussions also suggest IQOS is likely to be used to avoid clean air policies or used in areas in which smoking is restricted.

Analysis of the information management system in the manufacturing process of cigarette enterprises using fuzzy AHP

In view of the production quality management of filter rods in the manufacturing and execution process of cigarette enterprises, this paper analyzes the necessity of implementing the manufacturing execution system (MES) in the production process of filter rods. In this paper, the filter rod quality system of cigarette enterprise based on MES is fully studied, and the constructive information management system demand analysis, cigarette quality control process, system function module design, implementation and test effect are given. This paper utilizes the Fuzzy analytic hierarchy process to find the optimal system for processing the manufacturing of cigarette. The implementation of MSE based filter rod quality information management system for a cigarette enterprise ensures the quality control in the cigarette production process. Through visualization, real-time and dynamic way, the information management of cigarette production is completed, which greatly improves the quality of cigarette enterprise manufacturing process.

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.

E-Cigarette Advocates on Twitter: Content Analysis of Vaping-Related Tweets

Background

As the majority of Twitter content is publicly available, the platform has become a rich data source for public health surveillance, providing insights into emergent phenomena, such as vaping. Although there is a growing body of literature that has examined the content of vaping-related tweets, less is known about the people who generate and disseminate these messages and the role of e-cigarette advocates in the promotion of these devices.

Objective

This study aimed to identify key conversation trends and patterns over time, and discern the core voices, message frames, and sentiment surrounding e-cigarette discussions on Twitter.

Methods

A random sample of data were collected from Australian Twitter users who referenced at least one of 15 identified e-cigarette related keywords during 2012, 2014, 2016, or 2018. Data collection was facilitated by TrISMA (Tracking Infrastructure for Social Media Analysis) and analyzed by content analysis.

Results

A sample of 4432 vaping-related tweets posted and retweeted by Australian users was analyzed. Positive sentiment (3754/4432, 84.70%) dominated the discourse surrounding e-cigarettes, and vape retailers and manufacturers (1161/4432, 26.20%), the general public (1079/4432, 24.35%), and e-cigarette advocates (1038/4432, 23.42%) were the most prominent posters. Several tactics were used by e-cigarette advocates to communicate their beliefs, including attempts to frame e-cigarettes as safer than traditional cigarettes, imply that federal government agencies lack sufficient competence or evidence for the policies they endorse about vaping, and denounce as propaganda “gateway” claims of youth progressing from e-cigarettes to combustible tobacco. Some of the most common themes presented in tweets were advertising or promoting e-cigarette products (2040/4432, 46.03%), promoting e-cigarette use or intent to use (970/4432, 21.89%), and discussing the potential of e-cigarettes to be used as a smoking cessation aid or tobacco alternative (716/4432, 16.16%), as well as the perceived health and safety benefits and consequences of e-cigarette use (681/4432, 15.37%).

Conclusions

Australian Twitter content does not reflect the country’s current regulatory approach to e-cigarettes. Rather, the conversation on Twitter generally encourages e-cigarette use, promotes vaping as a socially acceptable practice, discredits scientific evidence of health risks, and rallies around the idea that e-cigarettes should largely be outside the bounds of health policy. The one-sided nature of the discussion is concerning, as is the lack of disclosure and transparency, especially among vaping enthusiasts who dominate the majority of e-cigarette discussions on Twitter, where it is unclear if comments are endorsed, sanctioned, or even supported by the industry.

Characterizing Social Media Messages Related to Underage JUUL E-Cigarette Buying and Selling: Cross-Sectional Analysis of Reddit Subreddits

Background

Stopping the epidemic of e-cigarette use among youth has become the common goal of both regulatory authorities and health departments. JUUL is currently the most popular e-cigarette brand on the market. Young people usually obtain and exchange information about JUUL with the help of social media platforms. Along with the rising prevalence of JUUL, posts about underage JUUL buying and selling have appeared on social media platforms such as Reddit, which sharply increase the risk of minors being exposed to JUUL.

Objective

This study aims to analyze Reddit messages about JUUL buying and selling among the users of the UnderageJuul subreddit, and to further summarize the characteristics of those messages. The findings and insights can contribute to a better understanding of the patterns of underage JUUL use, and help public health officials provide timely education and guidance to minors who have intentions of accessing JUUL.

Methods

We used a novel cross-subreddit method to analyze the Reddit messages on 2 subreddits. From July 9, 2017, to January 7, 2018, we collected data from the UnderageJuul subreddit, which was created for underage JUUL use discussion. The data set included 716 threads, 2935 comments, and 844 Reddit users (ie, Redditors). We collected our second data set, comprising 23,840 threads and 162,106 comments posted between July 9, 2017, and January 8, 2019, from the JUUL subreddit. We conducted analyses including the following: (1) annotation of users with buying/selling intention, (2) posting patterns discovery and topic comparison, and (3) posting activeness observation of discovered Redditors. Term frequency–inverse document frequency and regular expression-enhanced keyword search methods were applied during the content analysis to extract the posting patterns. The public posting records of the discovered users on the JUUL subreddit during the year after the UnderageJuul subreddit was shut down were analyzed to determine whether they were still active and interested in obtaining JUUL.

Results

Our study revealed the following: (1) Among the 716 threads on the UnderageJuul subreddit, there were 214 threads related to JUUL sale and 168 threads related to JUUL purchase, which accounted for 53.5% (382/714) of threads. (2) Among the 844 Redditors of the UnderageJuul subreddit, 23.82% (201/844) of users were annotated with buying intention, and 21.10% (178/844) of users were annotated with selling intention. There were 34 users with buying/selling intention that self-reported as being <21 years old. (3) The most common key phrases used in selling threads were “WTS,” “want to sell,” “for sale,” and “selling” (154/214, 72.0%). The most common key phrases used in buying threads were “look for/get JUUL/pods” (58/168, 34.5%) and “WTB” (53/168, 31.5%). (4) The most important concern that UnderageJuul Redditors had in obtaining JUULs was the price (311/1306, 23.81%), followed by the delivery service (68/1306, 5.21%). (5) The most popular flavors among the users with buying/selling intention were mango, cucumber, and mint. The flavor preferences remained consistent on both subreddits. Adverse symptoms related to the mango flavor were reported by 3 users on the JUUL subreddit. (6) In total, 24.4% (49/201) of users wanted to buy JUULs and 46.6% (83/178) of users wanted to sell JUULs, including 11 self-reported underage users, who also participated in the discussions on the JUUL subreddit. (7) Within one year of the UnderageJuul subreddit shutting down, there were 40 users who continued to post 186 threads on the JUUL subreddit, including 10 threads indicating buying/selling willingness that were posted shortly after the UnderageJuul subreddit was closed.

Conclusions

There were overlapping users active in the JUUL and UnderageJuul subreddits. The buying/selling-related content appeared in multiple venues with certain posting patterns from July 9, 2017, to January 7, 2018. Such content might lead to a high risk of health problems for minors, such as nicotine addiction. Based on these findings, this study provided some insights and suggestions that might contribute to the decision-making processes of regulators and public health officials.

A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study

Background

In recent years, flavored electronic cigarettes (e-cigarettes) have become popular among teenagers and young adults. Discussions about e-cigarettes and e-cigarette use (vaping) experiences are prevalent online, making social media an ideal resource for understanding the health risks associated with e-cigarette flavors from the users’ perspective.

Objective

This study aimed to investigate the potential associations between electronic cigarette liquid (e-liquid) flavors and the reporting of health symptoms using social media data.

Methods

A dataset consisting of 2.8 million e-cigarette–related posts was collected using keyword filtering from Reddit, a social media platform, from January 2013 to April 2019. Temporal analysis for nine major health symptom categories was used to understand the trend of public concerns related to e-cigarettes. Sentiment analysis was conducted to obtain the proportions of positive and negative sentiment scores for all reported health symptom categories. Topic modeling was applied to reveal the topics related to e-cigarettes and health symptoms. Furthermore, generalized estimating equation (GEE) models were used to quantitatively measure potential associations between e-liquid flavors and the reporting of health symptoms.

Results

Temporal analysis showed that the Respiratory category was consistently the most discussed health symptom category among all categories related to e-cigarettes on Reddit, followed by the Throat category. Sentiment analysis showed higher proportions of positive sentiment scores for all reported health symptom categories, except for the Cancer category. Topic modeling conducted on all health-related posts showed that 17 of the top 100 topics were flavor related. GEE models showed different associations between the reporting of health symptoms and e-liquid flavor categories, for example, lower association of the Beverage flavors with Respiratory compared with other flavors and higher association of the Fruit flavors with Cardiovascular than other flavors.

Conclusions

This study identified different potential associations between e-liquid flavors and the reporting of health symptoms using social media data. The results of this study provide valuable information for further investigation of the health effects associated with different e-liquid flavors.

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.

An Experimental Study of Nicotine Warning Statements in E-cigarette Tweets

INTRODUCTION

It is unclear whether warnings on electronic cigarette (e-cigarette) advertisements required by the US Food and Drug Administration (FDA) will apply to social media. Given the key role of social media in marketing e-cigarettes, we seek to inform FDA decision making by exploring how warnings on various tweet content influence perceived healthiness, nicotine harm, likelihood to try e-cigarettes, and warning recall.

METHODS

In this 2 × 4 between-subjects experiment participants viewed a tweet from a fictitious e-cigarette brand. Four tweet content versions (e-cigarette product, e-cigarette use, e-cigarette in social context, unrelated content) were crossed with two warning versions (absent, present). Adult e-cigarette users (N = 994) were recruited via social media ads to complete a survey and randomized to view one of eight tweets. Multivariable regressions explored effects of tweet content and warning on perceived healthiness, perceived harm, and likelihood to try e-cigarettes, and tweet content on warning recall. Covariates were tobacco and social media use and demographics.

RESULTS

Tweets with warnings elicited more negative health perceptions of the e-cigarette brand than tweets without warnings (p < .05). Tweets featuring e-cigarette products (p < .05) or use (p < .001) elicited higher warning recall than tweets featuring unrelated content.

CONCLUSIONS

This is the first study to examine warning effects on perceptions of e-cigarette social media marketing. Warnings led to more negative e-cigarette health perceptions, but no effect on perceived nicotine harm or likelihood to try e-cigarettes. There were differences in warning recall by tweet content. Research should explore how varying warning content (text, size, placement) on tweets from e-cigarette brands influences health risk perceptions.

IMPLICATIONS

FDA's 2016 ruling requires warnings on advertisements for nicotine-containing e-cigarettes, but does not specify whether this applies to social media. This study is the first to examine how e-cigarette warnings in tweets influence perceived healthiness and harm of e-cigarettes, which is important because e-cigarette brands are voluntarily including warnings on Twitter and Instagram. Warnings influenced perceived healthiness of the e-cigarette brand, but not perceived nicotine harm or likelihood to try e-cigarettes. We also saw higher recall of warning statements for tweets featuring e-cigarettes. Findings suggest that expanding warning requirements to e-cigarette social media marketing warrants further exploration and FDA consideration.

Detecting Lung Cancer Trends by Leveraging Real-World and Internet-Based Data: Infodemiology Study

Background

Internet search data on health-related terms can reflect people’s concerns about their health status in near real time, and hence serve as a supplementary metric of disease characteristics. However, studies using internet search data to monitor and predict chronic diseases at a geographically finer state-level scale are sparse.

Objective

The aim of this study was to explore the associations of internet search volumes for lung cancer with published cancer incidence and mortality data in the United States.

Methods

We used Google relative search volumes, which represent the search frequency of specific search terms in Google. We performed cross-sectional analyses of the original and disease metrics at both national and state levels. A smoothed time series of relative search volumes was created to eliminate the effects of irregular changes on the search frequencies and obtain the long-term trends of search volumes for lung cancer at both the national and state levels. We also performed analyses of decomposed Google relative search volume data and disease metrics at the national and state levels.

Results

The monthly trends of lung cancer-related internet hits were consistent with the trends of reported lung cancer rates at the national level. Ohio had the highest frequency for lung cancer-related search terms. At the state level, the relative search volume was significantly correlated with lung cancer incidence rates in 42 states, with correlation coefficients ranging from 0.58 in Virginia to 0.94 in Oregon. Relative search volume was also significantly correlated with mortality in 47 states, with correlation coefficients ranging from 0.58 in Oklahoma to 0.94 in North Carolina. Both the incidence and mortality rates of lung cancer were correlated with decomposed relative search volumes in all states excluding Vermont.

Conclusions

Internet search behaviors could reflect public awareness of lung cancer. Research on internet search behaviors could be a novel and timely approach to monitor and estimate the prevalence, incidence, and mortality rates of a broader range of cancers and even more health issues.

Perceptions and Sentiments About Electronic Cigarettes on Social Media Platforms: Systematic Review

Background

Electronic cigarettes (e-cigarettes) have been widely promoted on the internet, and subsequently, social media has been used as an important informative platform by e-cigarette users. Beliefs and knowledge expressed on social media platforms have largely influenced e-cigarette uptake, the decision to switch from conventional smoking to e-cigarette smoking, and positive and negative connotations associated with e-cigarettes. Despite this, there is a gap in our knowledge of people’s perceptions and sentiments on e-cigarettes as depicted on social media platforms.

Objective

This study aimed to (1) provide an overview of studies examining the perceptions and sentiments associated with e-cigarettes on social media platforms and online discussion forums, (2) explore people’s perceptions of e-cigarette therein, and (3) examine the methodological limitations and gaps of the included studies.

Methods

Searches in major electronic databases, including PubMed, Cumulative Index of Nursing and Allied Health Literature, EMBASE, Web of Science, and Communication and Mass Media Complete, were conducted using the following search terms: “electronic cigarette,” “electronic vaporizer,” “electronic nicotine,” and “electronic nicotine delivery systems” combined with “internet,” “social media,” and “internet use.” The studies were selected if they examined participants’ perceptions and sentiments of e-cigarettes on online forums or social media platforms during the 2007-2017 period.

Results

A total of 21 articles were included. A total of 20 different social media platforms and online discussion forums were identified. A real-time snapshot and characteristics of sentiments, personal experience, and perceptions toward e-cigarettes on social media platforms and online forums were identified. Common topics regarding e-cigarettes included positive and negative health effects, testimony by current users, potential risks, benefits, regulations associated with e-cigarettes, and attitude toward them as smoking cessation aids.

Conclusions

Although perceptions among social media users were mixed, there were more positive sentiments expressed than negative ones. This study particularly adds to our understanding of current trends in the popularity of and attitude toward e-cigarettes among social media users. In addition, this study identified conflicting perceptions about e-cigarettes among social media users. This suggests that accurate and up-to-date information on the benefits and risks of e-cigarettes needs to be disseminated to current and potential e-cigarette users via social media platforms, which can serve as important educational channels. Future research can explore the efficacy of social media–based interventions that deliver appropriate information (eg, general facts, benefits, and risks) about e-cigarettes.

Trial Registration

PROSPERO CRD42019121611; https://tinyurl.com/yfr27uxs

Electronic Cigarette Themes on Twitter: Dissemination Patterns and Relations with Online News and Search Engine Queries in South Korea

This study examines multiple aspects of e-cigarette mentions on different online media channels during the announcement and implementation of a cigarette tax increase policy in South Korea. It consists of three parts. First, a Naive Bayes classifier was used to sort 59,147 tweets about e-cigarettes into five pre-designated themes - promotion, health, policy, product evaluation, and price - and to determine their relative prevalence. Second, social network analysis was used to identify the themes' dissemination patterns. Third, the themes were examined for their associations with e-cigarette mentions in two other media channels - online news articles (n = 580) and search engine queries (64 weeks of Google Trends data). Results show that the most prevalent tweet theme was product evaluation, and the theme with the largest increase during the data collection period was promotion. Promotion-themed tweets were the least connected with tweets about the other five themes, while health-themed tweets were the most connected. Finally, product evaluation-themed tweets exhibited the strongest correlation with search engine query count and had the largest explanatory power.

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.

Combining Crowd-Sourcing and Automated Content Methods to Improve Estimates of Overall Media Coverage: Theme Mentions in E-cigarette and Other Tobacco Coverage

Exposure to media content can shape public opinions about tobacco. Accurately describing content is a first step to showing such effects. Historically, content analyses have hand-coded tobacco-focused texts from a few media sources which ignored passing mention coverage and social media sources, and could not reliably capture over-time variation. By using a combination of crowd-sourced and automated coding, we labeled the population of all e-cigarette and other tobacco-related (including cigarettes, hookah, cigars, etc.) 'long-form texts' (focused and passing coverage, in mass media and website articles) and social media items (tweets and YouTube videos) collected May 2014-June 2017 for four tobacco control themes. Automated coding of theme coverage met thresholds for item-level precision and recall, event validation, and weekly-level reliability for most sources, except YouTube. Health, Policy, Addiction and Youth themes were frequent in e-cigarette long-form focused coverage (44%-68%), but not in long-form passing coverage (5%-22%). These themes were less frequent in other tobacco coverage (long-form focused (13-32%) and passing coverage (4-11%)). Themes were infrequent in both e-cigarette (1-3%) and other tobacco tweets (2-4%). Findings demonstrate that passing e-cigarette and other tobacco long-form coverage and social media sources paint different pictures of theme coverage than focused long-form coverage. Automated coding also allowed us to code the amount of data required to estimate reliable weekly theme coverage over three years. E-cigarette theme coverage showed much more week-to-week variation than did other tobacco coverage. Automated coding allows accurate descriptions of theme coverage in passing mentions, social media, and trends in weekly theme coverage.

Participation in electronic cigarette-related social media communities: Effects on attitudes toward quitting, self-efficacy, and intention to quit

This study examined the effects of joining and actively participating in electronic-cigarette-related social media communities (SMCs), along with e-cigarette-related subjective norms, and social identification with other electronic-cigarette (e-cigarette) users, on current e-cigarette users' attitudes toward quitting, self-efficacy, and intention to quit. Results (n = 1016) indicated that greater e-cigarette-related social media use, more positive e-cigarette-related subjective norms and greater identification with other e-cigarette users, resulted in significantly more negative attitudes toward quitting, lower self-efficacy and lower intention to quit. E-cigarette-related social media use also interacted with subjective norms to influence intention to quit, and with identification with other e-cigarette users to influence self-efficacy.

Underage JUUL Use Patterns: Content Analysis of Reddit Messages

Background

The popularity of JUUL (an e-cigarette brand) among youth has recently been reported in news media and academic papers, which has raised great public health concerns. Little research has been conducted on the age distribution, geographic distribution, approaches to buying JUUL, and flavor preferences pertaining to underage JUUL users.

Objective

The aim of this study was to analyze social media data related to demographics, methods of access, product characteristics, and use patterns of underage JUUL use.

Methods

We collected publicly available JUUL-related data from Reddit. We extracted and summarized the age, location, and flavor preference of subreddit UnderageJuul users. We also compared common and unique users between subreddit UnderageJuul and subreddit JUUL. The methods of purchasing JUULs were analyzed by manually examining the content of the Reddit threads.

Results

A total of 716 threads and 2935 comments were collected from the subreddit UnderageJuul before it was shut down. Most threads did not mention a specific age, but ages ranged from 13 years to greater than 21 years in those that did. Mango, mint, and cucumber were the most popular among the 7 flavors listed on JUUL’s official website, and 336 subreddit UnderageJuul threads mentioned 7 discreet approaches to circumvent relevant legal regulations to get JUUL products, the most common of which was purchasing JUUL from other Reddit users (n=181). Almost half of the UnderageJuul users (389/844, 46.1%) also participated in discussions on the main JUUL subreddit and sought information across multiple Reddit forums. Most (64/74, 86%) posters were from large metropolitan areas.

Conclusions

The subreddit UnderageJuul functioned as a forum to explore methods of obtaining JUUL and to discuss and recommend specific flavors before it was shut down. About half of those using UnderageJuul also used the more general JUUL subreddit, so a forum still exists where youths can attempt to share information on how to obtain JUUL and other products. Exploration of such social media data in real time for rapid public health surveillance could provide early warning for significant health risks before they become major public health threats.

Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data

OBJECTIVE

We present a narrative review of recent work on the utilisation of Natural Language Processing (NLP) for the analysis of social media (including online health communities) specifically for public health applications.

METHODS

We conducted a literature review of NLP research that utilised social media or online consumer-generated text for public health applications, focussing on the years 2016 to 2018. Papers were identified in several ways, including PubMed searches and the inspection of recent conference proceedings from the Association of Computational Linguistics (ACL), the Conference on Human Factors in Computing Systems (CHI), and the International AAAI (Association for the Advancement of Artificial Intelligence) Conference on Web and Social Media (ICWSM). Popular data sources included Twitter, Reddit, various online health communities, and Facebook.

RESULTS

In the recent past, communicable diseases (e.g., influenza, dengue) have been the focus of much social media-based NLP health research. However, mental health and substance use and abuse (including the use of tobacco, alcohol, marijuana, and opioids) have been the subject of an increasing volume of research in the 2016 - 2018 period. Associated with this trend, the use of lexicon-based methods remains popular given the availability of psychologically validated lexical resources suitable for mental health and substance abuse research. Finally, we found that in the period under review "modern" machine learning methods (i.e. deep neural-network-based methods), while increasing in popularity, remain less widely used than "classical" machine learning methods.

Tobacco Use Behaviors, Attitudes, and Demographic Characteristics of Tobacco Opinion Leaders and Their Followers: Twitter Analysis

BACKGROUND

Tobacco-related content on social media is generated and propagated by opinion leaders on the Web who disseminate messages to others in their network, including followers, who then continue to spread the information. Opinion leaders can exert powerful influences on their followers' knowledge, attitudes, and behaviors; yet, little is known about the demographic characteristics and tobacco use behavior of tobacco opinion leaders on the Web and their followers, compared with general Twitter users.

OBJECTIVE

In this study, we hypothesized that opinion leaders use more tobacco products and have higher nicotine dependence than the other 2 groups (eg, followers and general Twitter users) and that followers-those who spread messages by opinion leaders-would more likely be in demographic groups that are vulnerable to tobacco marketing influence (eg, young adults and lower educational attainment).

METHODS

We constructed the social networks of people who tweet about tobacco and categorized them using a combination of social network and Twitter metrics. To understand the characteristics of tobacco opinion leaders and their followers, we conducted a survey of tobacco opinion leaders, their followers, and general Twitter users. The sample included 347 opinion leaders, 567 followers, and 519 general users. The opinion leaders had a median of 1000 followers, whereas followers and general users had fewer than 600 followers.

RESULTS

Opinion leaders were more likely than their followers to report past month use of tobacco products; followers, in turn, were more likely to report past month use of these products than general Twitter users. The followers appeared to be an especially vulnerable group; they tended to be younger (mean age 22.4 years) and have lower education compared with the opinion leaders and general users.

CONCLUSIONS

Followers of Twitter tobacco opinion leaders are a vulnerable group that might benefit from antitobacco education to counter the protobacco communications they see on social media.

"Technophilia": A new risk factor for electronic cigarette use among early adolescents?

PURPOSE

Develop and validate a scale that measures Technophilia (positive orientation toward new technology) and use it to address orientation toward new technologies to explain e-cigarette trial and adoption, especially in relatively low risk adolescents.

METHODS

Survey data were obtained from students of the three largest cities in Mexico (n = 8123). We developed eight questions involving access, use and pleasure from different electronic media to measure technophilia. Exploratory factor analysis (EFA) was conducted. Linear GEE models were used when regressing technophilia on covariates. When regressing e-cigarette and conventional cigarette trial and use, logistic GEE models were used. Finally, we used multinomial logistic regression to evaluate the associations between technophilia and e-cigarettes as the first tobacco product.

RESULTS

Technophilia were correlated with theoretically-related variables. Unadjusted and adjusted models regressing e-cigarette trial and use indicated that students in the highest quartile for technophilia were more likely to have tried e-cigarettes compared with the lowest quartile (AORQ4 vs Q1 = 1.36, 95% CI 1.14-1.62). Technophilia was not independently associated with current e-cigarette use in adjusted models. Students with higher technophilia were more likely to have first tried e-cigarettes in both crude and adjusted models (AORQ4vQ1 = 1.66, 95% CI 1.20-2.31; AORQ3vQ1 = 1.43, 95% CI 1.02-2.01). Technophilia did not have a statistically significant, independent association with first use of other tobacco products.

CONCLUSION

This study suggests that technophilia is associated with trial of e-cigarettes among youth. The measure we developed appears useful for understanding why some youth are open to trying novel, technologically oriented ways to consume nicotine.

Understanding the implications of the "vaping epidemic" among adolescents and young adults: A call for action

In the past 5 years, the use of nicotine delivered through electronic cigarettes ("e-cigarettes") has sky-rocketed among adolescents and young adults. E-cigarettes, with their high nicotine content, appealing flavors, low costs, wide availability, and discreet designs threaten 5 decades of progress in the fight against tobacco use. Aside from the increased risk of subsequent use of traditional cigarettes, marijuana, opioids, and other illicit drugs, building evidence indicates that e-cigarette use also exposes youth to several acute and long-term health risks that greatly outweigh the as-yet unfounded potential benefits from the use of e-cigarettes as a smoking reduction or cessation tool in this age group. We discuss some of the latest research on e-cigarettes, highlighting risks and harms associated with their use in adolescents and young adults, and suggest opportunities for action, including the enforcement of age, sales and marketing limitations, and concerted research and public health efforts to help curb what has become a new nicotine epidemic among youth.

Electronic cigarette usage patterns: a case study combining survey and social media data

Objective

To identify who were social media active e-cigarette users, to compare the use patterns from both survey and social media data for data triangulation, and to jointly use both datasets to conduct a comprehensive analysis on e-cigarette future use intentions.

Materials and Methods

We jointly used an e-cigarette use online survey (n = 5132) and a social media dataset. We conducted analysis from 3 different perspectives. We analyzed online forum participation patterns using survey data. We compared e-cigarette use patterns, including brand and flavor types, ratings, and purchase approaches, between the 2 datasets. We used logistic regression to study intentions to use e-cigarettes using both datasets.

Results

Male and younger e-cigarette users were the most likely to participate in e-cigarette-related discussion forums. Forum active survey participants were hardcore vapers. The e-cigarette use patterns were similar in the online survey data and the social media data. Intention to use e-cigarettes was positively related to e-liquid ratings and flavor ratings. Social media provided a valuable source of information on users' ratings of e-cigarette refill liquids.

Discussion

For hardcore vapers, social media data were consistent with online survey data, which suggests that social media may be useful to study e-cigarette use behaviors and can serve as a useful complement to online survey research. We proposed an innovative framework for social media data triangulation in public health studies.

Conclusion

We illustrated how social media data, combined with online survey data, can serve as a new and rich information source for public health research.

Relationship between social media engagement and e-cigarette policy support

Introduction

Given increasing efforts to regulate e-cigarettes, it is important to understand factors associated with support for tobacco regulatory policies. We investigate such factors found in social media and hypothesize that greater online engagement with tobacco content would be associated with less support for e-cigarette regulatory policies.

Methods

We constructed social networks of Twitter users who tweet about tobacco and categorized them using a combination of social network and Twitter metrics. Twitter users were identified as representing leaders, followers or general users in online discussions of tobacco products, and invited to complete an online survey. Participants responded to questions about their engagement with tobacco-related content online, degree of support for e-cigarette regulations, exposure to tobacco marketing, e-cigarette use and other demographic information. We examined links between their reported engagement with tobacco-related content and support for e-cigarette regulatory policies using structural equation modelling.

Results

The analytic sample consisted of 470 participants. The conceptualized structural equation model had a good fit (χ² (32) = 24.85, p = 0.09, CFI = 0.99, RMSEA = 0.03). Findings support our hypothesis: engagement with online tobacco content was negatively associated with support for e-cigarette policies, while controlling for e-cigarette use, tobacco marketing exposure, social media use frequency and demographic factors.

Conclusions

Findings suggest that our hypothesis was supported. Twitter users engaging with tobacco-related content and harboring negative attitudes toward e-cigarette regulatory policies could be an important audience segment to reach with tailored e-cigarette policy education messages.

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Online engagement associated with lower support for e-cigarette regulations.

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E-cigarette use, sex and income associated with support for e-cigarette regulations.

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Tobacco marketing exposure not associated with e-cigarette regulation support.

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Findings inform tobacco policy education campaign efforts.

A qualitative exploration of information-seeking by electronic nicotine delivery systems (ENDS) users in New Zealand

OBJECTIVES

Given recent increases in awareness and uptake of electronic nicotine delivery systems (ENDS), we aimed to explore ENDS users' information needs and search behaviours and whether information gaps exist.

DESIGN

Qualitative study using semistructured interviews that probed participants' smoking behaviours and ENDS use; data in this study examine ENDS information-seeking behaviours. We used qualitative description to analyse interview transcripts.

PARTICIPANTS AND SETTING

We recruited 39 current ENDS users (20 dual users and 19 exclusive ENDS users who reported having previously smoked cigarettes regularly) aged 18 and over, from three urban centres in New Zealand.

RESULTS

Several participants used Google to search for information on ENDS' health effects, but described the material they retrieved as vague or contradictory. Some interpreted the absence of information on long-term health effects as evidence ENDS did not pose potential health risks, and several perceived e-liquids as benign. Many relied on information sourced from other ENDS users, gleaned from online forums, YouTube or from discussions with friends and acquaintances; these sources typically presented ENDS positively. Several participants found specialist ENDS retailers provided valuable advice; non-specialist store staff generally lacked detailed product knowledge and sometimes offered inaccurate information.

CONCLUSION

People seeking information on ENDS' health effects are more likely to retrieve recommendations, product reviews and endorsements from online sources or through exchanges with other users, than they are to find scientific data. Health authorities could help meet potential users' information needs by, first, creating and frequently updating objective lay summaries of the latest scientific evidence; second, by mandating licensing for retailers with guidelines to disclose uncertainty over ENDS' efficacy for cessation and longer-term health effects, and the need for complete substitution of ENDS for combustible cigarettes among those who use these products.

Identification of Primary Medication Concerns Regarding Thyroid Hormone Replacement Therapy From Online Patient Medication Reviews: Text Mining of Social Network Data

BACKGROUND

Patients with hypothyroidism report poor health-related quality of life despite having undergone thyroid hormone replacement therapy (THRT). Understanding patient concerns regarding levothyroxine can help improve the treatment outcomes of THRT.

OBJECTIVE

This study aimed to (1) identify the distinctive themes in patient concerns regarding THRT, (2) determine whether patients have unique primary medication concerns specific to their demographics, and (3) determine the predictability of primary medication concerns on patient treatment satisfaction.

METHODS

We collected patient reviews from WebMD in the United States (1037 reviews about generic levothyroxine and 1075 reviews about the brand version) posted between September 1, 2007, and January 30, 2017. We used natural language processing to identify the themes of medication concerns. Multiple regression analyses were conducted in order to examine the predictability of the primary medication concerns on patient treatment satisfaction.

RESULTS

Natural language processing of the patient reviews of levothyroxine posted on a social networking site produced 6 distinctive themes of patient medication concerns related to levothyroxine treatment: how to take the drug, treatment initiation, dose adjustment, symptoms of pain, generic substitutability, and appearance. Patients had different primary medication concerns unique to their gender, age, and treatment duration. Furthermore, treatment satisfaction on levothyroxine depended on what primary medication concerns the patient had.

CONCLUSIONS

Natural language processing of text content available on social media could identify different themes of patient medication concerns that can be validated in future studies to inform the design of tailored medication counseling for improved patient treatment satisfaction.

Understanding Users' Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques

Background

E-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids—much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications.

Objective

This study aimed to understand users’ “vaping” experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production).

Methods

We collected e-liquid reviews on JuiceDB from June 27, 2013 to December 31, 2017 using its public application programming interface. The dataset contains 27,070 reviews for 8058 e-liquid products. Each review is accompanied by an overall rating and a set of 4 aspect ratings of an e-liquid, each on a scale of 1-5: flavor accuracy, throat hit, value, and cloud production. An iterative dichotomiser 3 (ID3)-based influential aspect analysis model was adopted to learn the key elements that impact e-liquid use. Then, fine-grained sentiment analysis was employed to mine opinions on various aspects of vaping experience related to e-liquids.

Results

We found that flavor accuracy and value were the two most important aspects that affected users’ sentiments toward e-liquids. Of reviews in JuiceDB, 67.83% (18,362/27,070) were positive, while 12.67% (3430/27,070) were negative. This indicates that users generally hold positive attitudes toward e-liquids. Among the 9 flavors, fruity and sweet were the two most popular. Great and sweet tastes, reasonable value, and strong throat hit made users satisfied with fruity and sweet flavors, whereas “strange” tastes made users dislike those flavors. Meanwhile, users complained about some e-liquids’ steep or expensive prices, bad quality, and harsh throat hit. There were 2342 fruity e-liquids and 2049 sweet e-liquids. There were 55.81% (1307/2342) and 59.83% (1226/2049) positive sentiments and 13.62% (319/2342) and 12.88% (264/2049) negative sentiments toward fruity e-liquids and sweet e-liquids, respectively. Great flavors and good vapors contributed to positive reviews of fruity and sweet products. However, bad tastes such as “sour” or “bitter” resulted in negative reviews. These findings can help businesses and policy makers to further improve product quality and formulate effective policy.

Conclusions

This study provides an effective mechanism for analyzing users’ ENDS vaping experience based on sentiment opinion summarization techniques. Sentiment opinions on aspect and products can be found using our method, which is of great importance to monitor e-liquid products and improve work efficiency.

E-cigarette advertising exposure in e-cigarette naïve adolescents and subsequent e-cigarette use: A longitudinal cohort study

OBJECTIVE

Electronic (E-) cigarettes are one of the most popular tobacco products used by adolescents today. This study examined whether exposure to advertisements in (1) social networking sites (Facebook, Twitter, YouTube, Pinterest/Google Plus), (2) traditional media (television/radio, magazines, billboards), or (3) retail stores (convenience stores, mall kiosks, tobacco shops) was associated with subsequent e-cigarette use in a longitudinal cohort of adolescents.

METHODS

Data were drawn from longitudinal surveys conducted in fall 2013 (wave 1) and spring 2014 (wave 2) of a school-based cohort attending 3 high schools and 2 middle schools in Connecticut. Adolescents were asked about tobacco use behaviors and where they had recently seen e-cigarette advertising at wave 1. We used logistic regression to determine whether advertising exposure at wave 1 increased the odds of e-cigarette use by wave 2, controlling for demographics and cigarette smoking status at wave 1.

RESULTS

Among those who have never used e-cigarettes in wave 1 (n = 1742), 9.6% reported e-cigarette use at wave 2. Multivariate logistic regression demonstrated that exposure to e-cigarette advertising on Facebook (OR 2.12 = p < 0.02) at wave 1, but not other venues, significantly increased the odds of subsequent e-cigarette use wave 2. Age, white race, and cigarette smoking at wave 1 also was associated with e-cigarette use at wave 2.

CONCLUSION

This study provides one of the first longitudinal examinations demonstrating that exposure to e-cigarette advertising on social networking sites among youth who had never used e-cigarettes increases the likelihood of subsequent e-cigarette use.

Mining Patients' Narratives in Social Media for Pharmacovigilance: Adverse Effects and Misuse of Methylphenidate

Background: The Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) have recognized social media as a new data source to strengthen their activities regarding drug safety.

Objective: Our objective in the ADR-PRISM project was to provide text mining and visualization tools to explore a corpus of posts extracted from social media. We evaluated this approach on a corpus of 21 million posts from five patient forums, and conducted a qualitative analysis of the data available on methylphenidate in this corpus.

Methods: We applied text mining methods based on named entity recognition and relation extraction in the corpus, followed by signal detection using proportional reporting ratio (PRR). We also used topic modeling based on the Correlated Topic Model to obtain the list of the matics in the corpus and classify the messages based on their topics.

Results: We automatically identified 3443 posts about methylphenidate published between 2007 and 2016, among which 61 adverse drug reactions (ADR) were automatically detected. Two pharmacovigilance experts evaluated manually the quality of automatic identification, and a f-measure of 0.57 was reached. Patient's reports were mainly neuro-psychiatric effects. Applying PRR, 67% of the ADRs were signals, including most of the neuro-psychiatric symptoms but also palpitations. Topic modeling showed that the most represented topics were related to Childhood and Treatment initiation, but also Side effects. Cases of misuse were also identified in this corpus, including recreational use and abuse.

Conclusion: Named entity recognition combined with signal detection and topic modeling have demonstrated their complementarity in mining social media data. An in-depth analysis focused on methylphenidate showed that this approach was able to detect potential signals and to provide better understanding of patients' behaviors regarding drugs, including misuse.

Evaluation of Advertising Campaigns on Social Media Networks

As the virtual environment is constantly changing, not only users’ informational and knowledge needs but also the means and channels of communication with customers applied by organizations change. There is a noticeable trend to move more and more advertising campaigns to social media networks because of the opportunities they provide to organizations and users, which results in the ever-increasing popularity of social media networks and a number of their users. Such a transition is explained by one of the main objectives organizations have: to inform their customers in an appropriate way and receive feedback on social media networks, which is difficult when traditional advertising channels and means are applied. Since advertising campaigns on social media networks are evolving rapidly, their assessment factors and methods, which receive controversial opinions in both scientific literature and practice, change too. Researchers assess and interpret the factors that influence the effectiveness of advertising campaigns on social media networks differently. Thus, a problem arises: how should we evaluate which approach is more capable of accurately and fully reflecting and conveying reality? In this research, this problem is studied by connecting approaches of different researchers. These approaches are linked to the effectiveness assessment of advertising campaigns on social media network aspects. To achieve the objective of this study, such research methods as analysis of scientific literature, multiple criteria and expert assessment (a structured survey and an interview) were applied. During the study, out of 39 primary assessment factors, eight primary factors that influence the effectiveness of advertising campaigns on social media networks were identified: sales, content reach, traffic to website, impressions, frequency, relevance score, leads and audience growth.

Raising Awareness About Cervical Cancer Using Twitter: Content Analysis of the 2015 #SmearForSmear Campaign

Background

Cervical cancer is the second most common cancer among women under 45 years of age. To deal with the decrease of smear test coverage in the United Kingdom, a Twitter campaign called #SmearForSmear has been launched in 2015 for the European Cervical Cancer Prevention Week. Its aim was to encourage women to take a selfie showing their lipstick going over the edge and post it on Twitter with a raising awareness message promoting cervical cancer screening. The estimated audience was 500 million people. Other public health campaigns have been launched on social media such as Movember to encourage participation and self-engagement. Their result was unsatisfactory as their aim had been diluted to become mainly a social buzz.

Objective

The objectives of this study were to identify the tweets delivering a raising awareness message promoting cervical cancer screening (sensitizing tweets) and to understand the characteristics of Twitter users posting about this campaign.

Methods

We conducted a 3-step content analysis of the English tweets tagged #SmearForSmear posted on Twitter for the 2015 European Cervical Cancer Prevention Week. Data were collected using the Twitter application programming interface. Their extraction was based on an analysis grid generated by 2 independent researchers using a thematic analysis, validated by a strong Cohen kappa coefficient. A total of 7 themes were coded for sensitizing tweets and 14 for Twitter users’ status. Verbatims were thematically and then statistically analyzed.

Results

A total of 3019 tweets were collected and 1881 were analyzed. Moreover, 69.96% of tweets had been posted by people living in the United Kingdom. A total of 57.36% of users were women, and sex was unknown in 35.99% of cases. In addition, 54.44% of the users had posted at least one selfie with smeared lipstick. Furthermore, 32.32% of tweets were sensitizing. Independent factors associated with posting sensitizing tweets were women who experienced an abnormal smear test (OR [odds ratio] 13.456, 95% CI 3.101-58.378, P<.001), female gender (OR 3.752, 95% CI 2.133-6.598, P<.001), and people who live in the United Kingdom (OR 2.097, 95% CI 1.447-3.038, P<.001). Nonsensitizing tweets were statistically more posted by a nonhealth or nonmedia company (OR 0.558, 95% CI 0.383-0.814, P<.001).

Conclusions

This study demonstrates that the success of a public health campaign using a social media platform depends on its ability to get its targets involved. It also suggests the need to use social marketing to help its dissemination. The clinical impact of this Twitter campaign to increase cervical cancer screening is yet to be evaluated.

What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer

Background

Social media dedicated to health are increasingly used by patients and health professionals. They are rich textual resources with content generated through free exchange between patients. We are proposing a method to tackle the problem of retrieving clinically relevant information from such social media in order to analyze the quality of life of patients with breast cancer.

Objective

Our aim was to detect the different topics discussed by patients on social media and to relate them to functional and symptomatic dimensions assessed in the internationally standardized self-administered questionnaires used in cancer clinical trials (European Organization for Research and Treatment of Cancer [EORTC] Quality of Life Questionnaire Core 30 [QLQ-C30] and breast cancer module [QLQ-BR23]).

Methods

First, we applied a classic text mining technique, latent Dirichlet allocation (LDA), to detect the different topics discussed on social media dealing with breast cancer. We applied the LDA model to 2 datasets composed of messages extracted from public Facebook groups and from a public health forum (cancerdusein.org, a French breast cancer forum) with relevant preprocessing. Second, we applied a customized Jaccard coefficient to automatically compute similarity distance between the topics detected with LDA and the questions in the self-administered questionnaires used to study quality of life.

Results

Among the 23 topics present in the self-administered questionnaires, 22 matched with the topics discussed by patients on social media. Interestingly, these topics corresponded to 95% (22/23) of the forum and 86% (20/23) of the Facebook group topics. These figures underline that topics related to quality of life are an important concern for patients. However, 5 social media topics had no corresponding topic in the questionnaires, which do not cover all of the patients’ concerns. Of these 5 topics, 2 could potentially be used in the questionnaires, and these 2 topics corresponded to a total of 3.10% (523/16,868) of topics in the cancerdusein.org corpus and 4.30% (3014/70,092) of the Facebook corpus.

Conclusions

We found a good correspondence between detected topics on social media and topics covered by the self-administered questionnaires, which substantiates the sound construction of such questionnaires. We detected new emerging topics from social media that can be used to complete current self-administered questionnaires. Moreover, we confirmed that social media mining is an important source of information for complementary analysis of quality of life.

Mining online e-liquid reviews for opinion polarities about e-liquid features

BACKGROUND

In recent years, the emerging electronic cigarette (e-cigarette) marketplace has developed prosperously all over the world. By analyzing online e-liquid reviews, we seek to identify the features attracting users.

METHODS

We collected e-liquid reviews from one of the largest online e-liquid review websites and extracted the e-liquid features by keywords. Then we used sentiment analysis to classify the features into two polarities: positive and negative. The positive sentiment ratio of a feature reflects the e-cigarette users' preference on this feature.

RESULTS

The popularity and preference of e-liquid features are not correlated. Nuts and cream are the favorite flavor categories, while fruit and cream are the most popular categories. The top mixed flavors are preferable to single flavors. Fruit and cream categories are most frequently mixed with other flavors. E-cigarette users are satisfied with cloud production, but not satisfied with the ingredients and throat hit.

CONCLUSIONS

We identified the flavors that e-cigarette users were satisfied with, and we found the users liked e-cigarette cloud production. Therefore, flavors and cloud production are potential factors attracting new users.