ArticleJournal of medical Internet research2020
Detection of Suicidality Among Opioid Users on Reddit: Machine Learning-Based Approach.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.
- Computational methods for the identification of suicidal ideation: a systematic review.Frontiers in artificial intelligence · 2026Pooled it
- TikTok is a valuable data source for tracking the opioid crisis.NPJ digital medicine · 2026Article
- Multi-label mental health classification in social media posts with multi-perspective prompt ensemble and auxiliary self-supervision.Scientific reports · 2025Article
- Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis.JMIR infodemiology · 2025Article
- Which social media platforms facilitate monitoring the opioid crisis?PLOS digital health · 2025Article
- Understanding Health-Related Discussions on Reddit: Development of a Topic Assignment Method and Exploratory Analysis.JMIR formative research · 2025Article
- Mining Suicidal Ideation in Chinese Social Media: A Dual-Channel Deep Learning Model with Information Gain Optimization.Entropy (Basel, Switzerland) · 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
- Automatically extracting social determinants of health for suicide: a narrative literature review.Npj mental health research · 2024Review
- The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review.JMIR infodemiology · 2024Article
- Predicting Suicidal Ideation, Planning, and Attempts among the Adolescent Population of the United States.Healthcare (Basel, Switzerland) · 2024Article
- Investigating Substance Use via Reddit: Systematic Scoping Review.Journal of medical Internet research · 2023Article
- Using Reddit as a recruitment strategy for addiction science research.Journal of substance use and addiction treatment · 2023Article
- Foreign pop-culture and backlash: the case of non-fan K-pop Subreddits during the pandemic.Journal of cultural economics · 2023Article
- Automatic Detection of Intimate Partner Violence Victims from Social Media for Proactive Delivery of Support.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Predicting Patient Satisfaction With Medications for Treating Opioid Use Disorder: Case Study Applying Natural Language Processing to Reviews of Methadone and Buprenorphine/Naloxone on Health-Related Social Media.JMIR infodemiology · 2023Article
- Leveraging Reddit for Suicidal Ideation Detection: A Review of Machine Learning and Natural Language Processing Techniques.International journal of environmental research and public health · 2022Review
- Natural language processing applied to mental illness detection: a narrative review.NPJ digital medicine · 2022Review
- Types and Sources of Stigma on Opioid Use Treatment and Recovery Communities on Reddit.Substance use & misuse · 2022Article
- Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action.Translational research : the journal of laboratory and clinical medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years, both suicide and overdose rates have been increasing. Many individuals who struggle with opioid use disorder are prone to suicidal ideation; this may often result in overdose. However, these fatal overdoses are difficult to classify as intentional or unintentional. Intentional overdose is difficult to detect, partially due to the lack of predictors and social stigmas that push individuals away from seeking help. These individuals may instead use web-based means to articulate their concerns.
objectiveThis study aimed to extract posts of suicidality among opioid users on Reddit using machine learning methods. The performance of the models is derivative of the data purity, and the results will help us to better understand the rationale of these users, providing new insights into individuals who are part of the opioid epidemic.
methodsReddit posts between June 2017 and June 2018 were collected from r/suicidewatch, r/depression, a set of opioid-related subreddits, and a control subreddit set. We first classified suicidal versus nonsuicidal languages and then classified users with opioid usage versus those without opioid usage. Several traditional baselines and neural network (NN) text classifiers were trained using subreddit names as the labels and combinations of semantic inputs. We then attempted to extract out-of-sample data belonging to the intersection of suicide ideation and opioid abuse. Amazon Mechanical Turk was used to provide labels for the out-of-sample data.
resultsClassification results were at least 90% across all models for at least one combination of input; the best classifier was convolutional neural network, which obtained an F
conclusionsOpioid abuse is linked to the risk of unintentional overdose and suicide risk. Social media platforms such as Reddit contain metadata that can aid machine learning and provide information at a personal level that cannot be obtained elsewhere. We demonstrate that it is possible to use NNs as a tool to predict an out-of-sample target with a model built from data sets labeled by characteristics we wish to distinguish in the out-of-sample target.
Indexed as
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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.