Evidence map›Paper›PMID 39269743›Full record

ArticleJMIR infodemiology2024

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

Alexandra Almeida, Thomas Patton, Mike Conway, Amarnath Gupta, Steffanie A Strathdee, Annick Bórquez

Abstract readScoping Review
In one paragraph

Article in JMIR infodemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alexandra Almeida *Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.ORCID 0000-0003-2092-5070
Thomas Patton *Department of Medicine, University of California San Diego, San Diego, CA, United States.ORCID 0000-0002-5134-3308
Mike ConwaySchool of Computing and Information Systems, The University of Melbourne, Melbourne, Australia.ORCID 0000-0002-3209-8108
Amarnath GuptaSan Diego Supercomputer Center, University of California San Diego, San Diego, CA, United States.ORCID 0000-0003-0897-120X
Steffanie A StrathdeeDepartment of Medicine, University of California San Diego, San Diego, CA, United States.ORCID 0000-0002-7724-691X
Annick BórquezDepartment of Medicine, University of California San Diego, San Diego, CA, United States.ORCID 0000-0002-6033-9837

Funding

VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUSAN JANET LITTLE · 1994 to 2026
$78.4M
Training Program in Substance Use, HIV and Related InfectionsT32DA023356 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Natasha Martin, Steffanie A Strathdee · 2007 to 2026
$7.8M
Real-time prediction of emerging drug use epidemics in the United StatesDP2DA049295 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BORQUEZ, ANNICK · 2019 to 2019
$2.4M
Using Narratives to Identify Stigma Phenotypes - A Socio-Ecological ApproachR21DA056684 · NIDA · UNIVERSITY OF WASHINGTON · PI CHEN, ANNIE · 2022 to 2023
$489k
NIAID NIH HHS P30 AI036214NIDA NIH HHS DP2 DA049295NIDA NIH HHS R21 DA056684NIDA NIH HHS T32 DA023356
6 · The paper itself

Abstract

backgroundThe 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.

objectiveWe aimed to understand how NLP has been applied to Reddit (Reddit Inc) data to study opioid use.

methodsWe 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.

resultsIn 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.

conclusionsThis 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.

Indexed as

Natural Language ProcessingSocial MediaAnalgesics, OpioidHumansOpioid-Related DisordersAnalgesics, Opioidmachine learningnatural language processingNLPopioidReddit

Identifiers

PMID39269743
PMCPMC11437337

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.