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

How to apply zero-shot learning to text data in substance use research: An overview and tutorial with media data

A vast amount of media-related text data is generated daily in the form of social media posts, news stories or academic articles. These text data provide opportunities for researchers to analyse and understand how substance-related issues are being discussed. The main methods to analyse large text data (content analyses or specifically trained deep-learning models) require substantial manual annotation and resources. A machine-learning approach called 'zero-shot learning' may be quicker, more flexible and require fewer resources. Zero-shot learning uses models trained on large, unlabelled (or weakly labelled) data sets to classify previously unseen data into categories on which the model has not been specifically trained. This means that a pre-existing zero-shot learning model can be used to analyse media-related text data without the need for task-specific annotation or model training. This approach may be particularly important for analysing data that is time critical. This article describes the relatively new concept of zero-shot learning and how it can be applied to text data in substance use research, including a brief practical tutorial.

Examining the Peer-Reviewed Literature on Tobacco-Related Social Media Data: Scoping Review

INTRODUCTION

Tobacco researchers have used social media data to examine tobacco industry marketing practices (eg, influencers), and to document user experience with tobacco products. This study summarized the literature that analyzed tobacco-related social media data, including domain, social media platform, tobacco product type, and themes of findings, among other variables.

AIMS AND METHODS

PubMed, PsycINFO, Web of Science, and Communication Source were searched between 2004 and 2022. Peer-reviewed articles were included if they were written in English, included at least one tobacco-related term, and one social media-related term, and analyzed a social media post. Two coders screened all-titles and abstracts. The final sample consisted of (n = 255) articles. Studies were coded for domain, social media platform, tobacco product type, data source, type of data, coding and analytic method, and presence of validation procedure, among other variables.

RESULTS

A total of 10 504 820 581 tobacco-related social media posts were assessed across 255 studies. User experience (54.1%) and promotion (23.1%) were the most researched domains. Researchers used data from Twitter the most (42.7%). Text (43.1%) was the most common type of data analyzed. Thematic analysis (80.8%) was the most common analytic technique. Themes of findings from content analyses often pertained to the health effects of tobacco use (61.0%) and promotion (44.2%).

CONCLUSIONS

Researchers have analyzed billions of tobacco-related social media posts to describe user experience with, and promotions related to, tobacco products like e-cigarettes on platforms like Twitter. Future research may examine tobacco-related social media data from newer platforms like TikTok.

IMPLICATIONS

Real-time surveillance of tobacco-related content on social media can keep the tobacco control community abreast of tobacco industry promotional strategies, user experience with tobacco products, and perceived health effects of tobacco use. A framework may be developed to establish best-practices for social media data collection and analysis, including strategies to identify posts from bot accounts and validate methodological approaches used in thematic analysis.

Keeping you connected or keeping you addicted? Weekly use of social media platforms is associated with hazardous alcohol use and problem gambling among adults

AIMS

A wide variety of social media platforms exist, each offering tailored solutions to attract specific target audiences based on their social media needs and interests. This diversity may pose a risk factor for the development or perpetuation of harmful behaviors. Research has established a connection between social media use and increased health risk behaviors. This six-wave exploratory longitudinal study investigated the associations between active social media use, hazardous alcohol use, and problem gambling among adult social media users.

METHODS

Data were collected via surveys in 6-month intervals, starting in March-April 2021 (T1: N = 1530; Mage = 46.67; SD = 16.42; 50.33% male). Of the T1 respondents, 58.10% participated in T6 (n = 889). Measures included the frequency of use of different social media platforms, the 3-item Alcohol Use Disorders Identification Test (AUDIT-C), and the Problem Gambling Severity Index (PGSI). Hybrid multilevel regression models were used for analyses.

RESULTS

We found positive within-person effects of weekly Facebook use and between-person effects of weekly use of Facebook, TikTok, and gambling-related online communities on drinking. These results suggest an increase in hazardous alcohol consumption over time among the platforms' active users. Weekly Instagram use had a negative between-person effect on hazardous alcohol use. Individuals using TikTok or gambling communities weekly were more prone to problem gambling compared to non-weekly users.

CONCLUSIONS

There are risks involved in the active use of some social media services among adult users. Prevention work, including digital health interventions, should be targeted according to the appropriate user group.

Rolling through TikTok: An analysis of 3,4-methylenedioxymethamphetamine-related content

INTRODUCTION

TikTok has quickly gained popularity through its platforming of large amounts of short video content. Given its widespread popularity, unrestricted access and poor content monitoring may allow 3,4-methylenedioxymethamphetamine (MDMA)-related content to influence perception of MDMA use. We aimed to investigate how MDMA-related videos are portrayed on TikTok and explore MDMA-related harm reduction content.

METHODS

MDMA-related hashtags and sounds were utilised to collect data from TikTok (n = 498). Video views, likes, comments and shares were recorded and quantified, and videos were coded for depiction/sentiment towards MDMA and thematic content.

RESULTS

The total sample view count was 82,413,781. Videos had a median view count of 28,900 (SD = ±561,645), median like count of 2269 (SD = ±102,904), median comment count of 52 (SD = ±755), and median share count of 34 (SD = ±3292). Most videos depicted MDMA neutrally (40.6%), while 34.9% were positive. MDMA intoxication was presumed in 40.2% of videos. The analysis produced seven themes, of which humour was the most common (80.5%). Harm reduction content was present in nine videos, viewed 999,700 times, and consisted of mixed subject matter.

DISCUSSION AND CONCLUSIONS

Similar themes and issues surrounding drug-related content on TikTok are relevant to MDMA, and intoxication was present in a significant portion of the sample. Better monitoring or regulation of content could potentially offset harm that may arise from consumption of such content. Promotion of harm reduction content could also be trialled to minimise harm.

Viral Vaping: A systematic review and meta analysis of e-cigarette and Tobacco-Related social media content and its influence on youth behaviours and attitudes

AIMS

E-cigarette and tobacco-related content on social media continues to rise from lax restrictions on both personal and promotional posts. This content has been linked to various mechanisms of increased e-cigarette and tobacco use (i.e., lower risk perceptions and increased susceptibility). This study aimed to synthesis the association between exposure to e-cigarette and tobacco-related content and youth behaviours and attitudes.

METHODS

A comprehensive search was conducted on PubMed, Scopus, PsycINFO and Web of Science. Studies published post-2004 reporting effect estimates for exposure or engagement with e-cigarette or tobacco content on social media and behaviour or attitude outcomes were included.

RESULTS

Thirty-two studies (N = 274,283, aged 9 to 25 years) were included for synthesis. Meta-analyses revealed significant associations between engagement with tobacco content and use (OR 2.21; 95% CI = 1.27-3.82, p =.005; I2 = 96.4%), exposure to tobacco content and never users' lower risk perceptions (OR 0.68; 95% CI = 0.49-0.91; p =.011; I2 = 78.2%), and exposure to e-cigarette content and use (OR 1.37; 95% CI = 0.99-1.88; p = 0.058; I2 = 64.4%). There was no observed relationship between exposure to tobacco content and ever users' risk perceptions (OR 0.83; 95% CI = 0.61-1.13; p =.231; I2 = 83.5%). Qualitative synthesis found significant associations between tobacco exposure and increased current use and pro-tobacco attitudes; e-cigarette exposure and increased susceptibility and lower risk perceptions; tobacco engagement and increased susceptibility; e-cigarette engagement and increased use; dual exposure and increased susceptibility; and dual engagement and increased dual use. Mixed findings were identified for the influence of e-cigarette exposure on attitudes, tobacco exposure on susceptibility, dual exposure on dual use behaviours, and dual engagement on dual susceptibility.

CONCLUSIONS

Findings suggest an association between exposure and engagement to e-cigarette or tobacco products on social media and use or pro-use attitudes among youth. Further substantive research in the area of youth-specific use and attitudes following exposure and engagement with e-cigarette and tobacco content is needed to quantify this association.

Results and Methodological Implications of the Digital Epidemiology of Prescription Drug References Among Twitter Users: Latent Dirichlet Allocation (LDA) Analyses

BACKGROUND

Social media is an important information source for a growing subset of the population and can likely be leveraged to provide insight into the evolving drug overdose epidemic. Twitter can provide valuable insight into trends, colloquial information available to potential users, and how networks and interactivity might influence what people are exposed to and how they engage in communication around drug use.

OBJECTIVE

This exploratory study was designed to investigate the ways in which unsupervised machine learning analyses using natural language processing could identify coherent themes for tweets containing substance names.

METHODS

This study involved harnessing data from Twitter, including large-scale collection of brand name (N=262,607) and street name (N=204,068) prescription drug-related tweets and use of unsupervised machine learning analyses (ie, natural language processing) of collected data with data visualization to identify pertinent tweet themes. Latent Dirichlet allocation (LDA) with coherence score calculations was performed to compare brand (eg, OxyContin) and street (eg, oxys) name tweets.

RESULTS

We found people discussed drug use differently depending on whether a brand name or street name was used. Brand name categories often contained political talking points (eg, border, crime, and political handling of ongoing drug mitigation strategies). In contrast, categories containing street names occasionally referenced drug misuse, though multiple social uses for a term (eg, Sonata) muddled topic clarity.

CONCLUSIONS

Content in the brand name corpus reflected discussion about the drug itself and less often reflected personal use. However, content in the street name corpus was notably more diverse and resisted simple LDA categorization. We speculate this may reflect effective use of slang terminology to clandestinely discuss drug-related activity. If so, straightforward analyses of digital drug-related communication may be more difficult than previously assumed. This work has the potential to be used for surveillance and detection of harmful drug use information. It also might be used for appropriate education and dissemination of information to persons engaged in drug use content on Twitter.

Seeing is believing: How cannabis marketing exposure is associated with cannabis use attitudes and behavior in a permissive medical cannabis policy environment

BACKGROUND AND OBJECTIVES

Oklahoma has a fast-growing medical cannabis industry, showing a proliferation of industry marketing. While cannabis marketing exposure (CME) is a risk factor for cannabis use and positive attitudes about use, no studies have examined the impact of CME on attitudes and use behavior in a permissive cannabis policy environment, like Oklahoma.

METHODS

N = 5428 Oklahoma adults ages 18 and older completed assessments of demographics, past 30-day cannabis use, and past 30-day exposure to each of four types of cannabis marketing: outdoor (billboards, signs), social media, print (magazines), and Internet. Regression models examined associations of CME with positive attitudes towards cannabis use, cannabis harm perceptions, interest in obtaining a medical cannabis license (among nonlicensed participants), and past 30-day cannabis use.

RESULTS

Three quarters (74.5%) reported any past 30-day CME. Outdoor CME was most prevalent (61.1%), followed by social media (46.5%), Internet (46.1%), and print (35.2%). Correlates of CME included younger age, higher educational attainment and income, and medical cannabis license. In adjusted regression models, past 30-day CME and number of sources of CME were associated with current cannabis use behavior, positive attitudes about cannabis, lower cannabis harm perceptions, and greater interest in obtaining a medical cannabis license. Similar associations between CME and positive attitudes about cannabis were shown among noncannabis users.

DISCUSSION AND CONCLUSIONS

Public health messaging should be employed to minimize the potential adverse impacts of CME.

SCIENTIFIC SIGNIFICANCE

No studies have examined correlates of CME in a rapidly growing and relatively unrestrained marketing environment.

Using Social Media to Examine Themes Surrounding Fentanyl Misuse and Risk Indicators

Background: Opioid misuse is a crisis in the United States, and synthetic opioids such as fentanyl pose risks for overdose and mortality. Individuals who misuse substances commonly seek information and support online due to stigma and legal concerns, and this online networking may provide insight for substance misuse prevention and treatment. We aimed to characterize topics in substance-misuse related discourse among members of an online fentanyl community. Method: We investigated posts on a fentanyl-specific forum on the platform Reddit to identify emergent substance misuse-related themes potentially indicative of heightened risk for overdose and other adverse health outcomes. We analyzed 27 posts and 338 comments with a qualitative codebook established using a subset of user posts via inductive and deductive methods. Posts and comments were independently reviewed by two coders with a third coder resolving discrepancies. The top 200 subreddits with the most activity by r/fentanyl members were also inductively analyzed to understand interests of r/fentanyl users. Results: Functional/quality of life impairments due to substance misuse (29%) was the most commonly occurring theme, followed by polysubstance use (27%) and tolerance/dependence/withdrawal (20%). Additional themes included drug identification with photos, substances cut with other drugs, injection drugs, and past overdoses. Media-focused subreddits and other drug focused communities were among the communities most often followed by r/fentanyl users. Conclusion: Themes closely align with DSM-V substance use disorder symptoms for fentanyl and other substances. High involvement in media-focused subreddits and other substance-misuse-related communities suggests digital platforms as acceptable for overdose prevention and recovery support interventions.