Tones and themes in Reddits posts discussing the opioid epidemic

Ramachandran, Shyam; Brown, Laura; Ring, David

doi:10.1080/10550887.2022.2049170

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…Of all shortlisted social media platforms, X (formerly Twitter) and Reddit were by far the most commonly used in existing literature. The topics of studies using these two platforms range from correlating opioid-related discussion volume and opioid-related overdose death rates (2,(7)(8)(9)(10)41,42,70,71), characterizing trends and themes in online discussion of OUD and OUD treatment (4,27,(37)(38)(39)(40)70,74,87,(103)(104)(105)(106)(107)(108)(109)(110)(111)(112)(113)(114)(115)(116)(117)(118)(119)(120)(121), and characterizing public sentiment towards the opioid epidemic generally (39,82,93,108,122,123). Many research groups have also created models to automatically identify posts on X and Reddit with discussion related to opioids.…”

Section: Prior Use In Research Literaturementioning

confidence: 99%

Which Social Media Platforms Provide the Most Informative Data for Monitoring the Opioid Crisis?

Carpenter,

Nguyen,

Smith

et al. 2024

Preprint

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Background and AimsSocial media can provide real-time insight into trends in substance use, addiction, and recovery. Prior studies have leveraged data from platforms such as Reddit and X (formerly Twitter), but evolving policies around data access have threatened their usability in opioid overdose surveillance systems. Here, we evaluate the potential of a broad set of platforms to detect emerging trends in the opioid crisis.DesignWe identified 72 online platforms with a substantial global user base or prior citations in opioid-related research. We evaluated each platform’s fit with our definition of social media, size of North American user base, and volume of opioid-related discourse. We created a shortlist of 11 platforms that met our criteria. We documented basic characteristics, volume and nature of opioid discussion, official policies regulating drug-related discussion, and data accessibility of shortlisted platforms.SettingUSA and Canada.MeasurementsWe quantified the volume of opioid discussion by number of platform-specific Google search hits for opioid terms. We captured informal language by including slang generated using a large language model. We report the number of opioid-related hits and proportion of opioid-related hits to hits for common nouns.FindingsWe found that TikTok, YouTube, and Facebook have the most potential for use in opioid-related surveillance. TikTok and Facebook have the highest relative amount of drug-related discussions. Language on TikTok was predominantly informal. Many platforms offer data access tools for research, but changing company policies and user norms create instability. The demographics of users varies substantially across platforms.ConclusionsSocial media data sources hold promise for detecting trends in opioid use, but researchers must consider the utility, accessibility, and stability of data on each platform. A strategy mixing several platforms may be required to cover all demographics suffering in the epidemic.

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Section: Prior Use In Research Literaturementioning

confidence: 99%

Which Social Media Platforms Provide the Most Informative Data for Monitoring the Opioid Crisis?

Carpenter,

Nguyen,

Smith

et al. 2024

Preprint

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The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review

Almeida,

Patton,

Conway

et al. 2024

JMIR Infodemiology

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Background The growing availability of big data spontaneously generated by social media platforms allows us to leverage natural language processing (NLP) methods as valuable tools to understand the opioid crisis. Objective We aimed to understand how NLP has been applied to Reddit (Reddit Inc) data to study opioid use. Methods We systematically searched for peer-reviewed studies and conference abstracts in PubMed, Scopus, PsycINFO, ACL Anthology, IEEE Xplore, and Association for Computing Machinery data repositories up to July 19, 2022. Inclusion criteria were studies investigating opioid use, using NLP techniques to analyze the textual corpora, and using Reddit as the social media data source. We were specifically interested in mapping studies’ overarching goals and findings, methodologies and software used, and main limitations. Results In total, 30 studies were included, which were classified into 4 nonmutually exclusive overarching goal categories: methodological (n=6, 20% studies), infodemiology (n=22, 73% studies), infoveillance (n=7, 23% studies), and pharmacovigilance (n=3, 10% studies). NLP methods were used to identify content relevant to opioid use among vast quantities of textual data, to establish potential relationships between opioid use patterns or profiles and contextual factors or comorbidities, and to anticipate individuals’ transitions between different opioid-related subreddits, likely revealing progression through opioid use stages. Most studies used an embedding technique (12/30, 40%), prediction or classification approach (12/30, 40%), topic modeling (9/30, 30%), and sentiment analysis (6/30, 20%). The most frequently used programming languages were Python (20/30, 67%) and R (2/30, 7%). Among the studies that reported limitations (20/30, 67%), the most cited was the uncertainty regarding whether redditors participating in these forums were representative of people who use opioids (8/20, 40%). The papers were very recent (28/30, 93%), from 2019 to 2022, with authors from a range of disciplines. Conclusions This scoping review identified a wide variety of NLP techniques and applications used to support surveillance and social media interventions addressing the opioid crisis. Despite the clear potential of these methods to enable the identification of opioid-relevant content in Reddit and its analysis, there are limits to the degree of interpretive meaning that they can provide. Moreover, we identified the need for standardized ethical guidelines to govern the use of Reddit data to safeguard the anonymity and privacy of people using these forums.

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The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review (Preprint)

Almeida,

Patton,

Conway

et al. 2023

Preprint

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BACKGROUND The growing availability of big data spontaneously generated by social media platforms leverages natural language processing (NLP) methods as valuable tools to understand the opioid crisis. OBJECTIVE We aimed to understand how NLP has been applied to Reddit data to study opioid use. METHODS We systematically searched for peer-reviewed studies and conference abstracts in PubMed, Scopus, PsychInfo, ACL Anthology, IEEE, and ACM data repositories, until July 19th, 2022. Inclusion criteria were studies (i) investigating opioid use, (ii) using NLP techniques to analyze the textual corpora, and (iii) using Reddit as the social media data source. We were specifically interested in mapping studies’ (a) overarching goals and findings, (b) methodologies and software used, and (c) main limitations. RESULTS Thirty studies were included, which were classified into four non-mutually exclusive “overarching goal” categories: methodological (six studies), infodemiology (twenty-two studies), infoveillance (seven studies), and pharmacovigilance (three studies). NLP methods were used to identify content relevant to opioid use among vast quantities of textual data, to establish potential relationships between opioid use patterns/profiles and contextual factors or comorbidities, and to anticipate individuals’ transitions between different opioid-related subreddits, likely revealing progression through opioid use stages. Most studies employed an embedding technique (12/30), prediction/classification approach (12/30), topic modeling (9/30), and sentiment analysis (6/30). The most frequently used programming languages were Python (20/30) and R (2/30). Among the studies that reported limitations (20/30), the most cited was the uncertainty regarding whether Redditors participating in these forums were representative of people who use opioids (8/20). The papers were very recent (28/30 were from 2019 to 2022), with authors from a range of disciplines. CONCLUSIONS This scoping review identified a wide variety of NLP techniques and applications used to support surveillance and social media interventions addressing the opioid crisis. Despite the clear potential of these methods to enable the identification of opioid-relevant content in Reddit and its analysis, there are limits to the degree of interpretive meaning that they can provide. Moreover, we identified the need for standardized ethical guidelines to govern the utilization of Reddit data to safeguard the anonymity and privacy of people using these forums. CLINICALTRIAL

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Tones and themes in Reddits posts discussing the opioid epidemic

Cited by 3 publications

References 8 publications

Which Social Media Platforms Provide the Most Informative Data for Monitoring the Opioid Crisis?

Which Social Media Platforms Provide the Most Informative Data for Monitoring the Opioid Crisis?

The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review

The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review (Preprint)

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