ReviewJournal of the American Medical Informatics Association : JAMIA2020
Mining social media for prescription medication abuse monitoring: a review and proposal for a data-centric framework.
Review in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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.
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.
Who cites it
20 citing papers in PubMed.
- Methods for Detecting Suspicious Information From Individual Transactions of Pharmaceutical Products via Twitter (now X): Retrospective Observational Study.Journal of medical Internet research · 2026Observational
- Topic and Sentiment Trends in Semaglutide Discussions on X: Subpopulation-Based Longitudinal Analysis.Online journal of public health informatics · 2026Article
- Inference Gap in Domain Expertise and Machine Intelligence in Named Entity Recognition: Creation of and Insights from a Substance Use-related Dataset.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- Monitoring the opioid epidemic via social media discussions.NPJ digital medicine · 2025Article
- Large-Scale Analysis of Online Questions Related to Opioid Use Disorder on Reddit.Proceedings of the ... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media · 2025Article
- First-hand accounts of structural stigma toward people who use opioids on Reddit.Social science & medicine (1982) · 2024Article
- Growing pains with kratom: experiences discussed in subreddits contrast with satisfaction expressed in surveys.Frontiers in pharmacology · 2024Article
- Social media and internet search data to inform drug utilization: A systematic scoping review.Frontiers in digital health · 2023Article
- Consumer-Generated Discourse on Cannabis as a Medicine: Scoping Review of Techniques.Journal of medical Internet research · 2022Article
- Spontaneously generated online patient experience data - how and why is it being used in health research: an umbrella scoping review.BMC medical research methodology · 2022Article
- SEED: Symptom Extraction from English Social Media Posts using Deep Learning and Transfer Learning.medRxiv : the preprint server for health sciences · 2022Article
- Large-Scale Social Media Analysis Reveals Emotions Associated with Nonmedical Prescription Drug Use.Health data science · 2022Article
- Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach.Journal of medical Internet research · 2021Article
- COVID-19 Pandemic Impact on Substance Misuse: A Social Media Listening, Mixed Method Analysis.Brain sciences · 2021Article
- Article
- Utilizing a multi-class classification approach to detect therapeutic and recreational misuse of opioids on Twitter.Computers in biology and medicine · 2021Article
- Text classification models for the automatic detection of nonmedical prescription medication use from social media.BMC medical informatics and decision making · 2021Article
- Whether the weather will help us weather the COVID-19 pandemic: Using machine learning to measure twitter users' perceptions.International journal of medical informatics · 2021Article
- Use of Social Media for Pharmacovigilance Activities: Key Findings and Recommendations from the Vigi4Med Project.Drug safety · 2020Article
- Social Media Mining Toolkit (SMMT).Genomics & informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
objectivePrescription medication (PM) misuse and abuse is a major health problem globally, and a number of recent studies have focused on exploring social media as a resource for monitoring nonmedical PM use. Our objectives are to present a methodological review of social media-based PM abuse or misuse monitoring studies, and to propose a potential generalizable, data-centric processing pipeline for the curation of data from this resource. MATERIALS AND
methodsWe identified studies involving social media, PMs, and misuse or abuse (inclusion criteria) from Medline, Embase, Scopus, Web of Science, and Google Scholar. We categorized studies based on multiple characteristics including but not limited to data size; social media source(s); medications studied; and primary objectives, methods, and findings.
resultsA total of 39 studies met our inclusion criteria, with 31 (∼79.5%) published since 2015. Twitter has been the most popular resource, with Reddit and Instagram gaining popularity recently. Early studies focused mostly on manual, qualitative analyses, with a growing trend toward the use of data-centric methods involving natural language processing and machine learning. DISCUSSION: There is a paucity of standardized, data-centric frameworks for curating social media data for task-specific analyses and near real-time surveillance of nonmedical PM use. Many existing studies do not quantify human agreements for manual annotation tasks or take into account the presence of noise in data.
conclusionThe development of reproducible and standardized data-centric frameworks that build on the current state-of-the-art methods in data and text mining may enable effective utilization of social media data for understanding and monitoring nonmedical PM use.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.