ArticleAnnual review of biomedical data science2020
Mining Social Media Data for Biomedical Signals and Health-Related Behavior.
Article in Annual review of biomedical data science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled 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.
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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methodologies for Monitoring Mental Health on Twitter: Systematic Review.Journal of medical Internet research · 2023Pooled it
- A computationally efficient biomedical text processing framework for pharmacovigilance: integrating low-rank adaptation and interpretable AI for adverse drug reaction detection.Medical & biological engineering & computing · 2026Article
- myAURA: a personalized health library for epilepsy management via knowledge graph sparsification and visualization.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Interpersonal conflicts, social media use and depression associated with protests.Nature medicine · 2026Article
- Focused digital cohort selection from social media using the metric backbone of biomedical knowledge graphs.Journal of biomedical informatics · 2025Article
- Quantifying the impact of biobanks and cohort studies.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Which social media platforms facilitate monitoring the opioid crisis?PLOS digital health · 2025Article
- Challenges and opportunities for digital twins in precision medicine from a complex systems perspective.NPJ digital medicine · 2025Review
- Evaluating large language models for health-related text classification tasks with public social media data.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Novel Machine Learning HIV Intervention for Sexual and Gender Minority Young People Who Have Sex With Men (uTECH): Protocol for a Randomized Comparison Trial.JMIR research protocols · 2024Article
- Natural Language Processing for Digital Health in the Era of Large Language Models.Yearbook of medical informatics · 2024Review
- Communication inequalities and incomplete data hinder understanding of how social media affect vaccine uptake.BMJ (Clinical research ed.) · 2024Article
- Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs.PLoS computational biology · 2023Article
- "I Haven't Been Diagnosed, but I Should Be"-Insight Into Self-diagnoses of Common Mental Health Disorders: Cross-sectional Study.JMIR formative research · 2023Article
- Linking Individual-Level Facebook Posts With Psychological and Health Data in an Epidemiological Cohort: Feasibility Study.JMIR formative research · 2022Article
- Using social media listening and data mining to understand travellers' perspectives on travel disease risks and vaccine-related attitudes and behaviours.Journal of travel medicine · 2022Article
- Small cohort of patients with epilepsy showed increased activity on Facebook before sudden unexpected death.Epilepsy & behavior : E&B · 2022Article
- Engaging PatientsFrontiers in pharmacology · 2022Article
- The distance backbone of complex networks.Journal of complex networks · 2021Article
- Assessing vulnerability to psychological distress during the COVID-19 pandemic through the analysis of microblogging content.Future generations computer systems : FGCS · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Social media data have been increasingly used to study biomedical and health-related phenomena. From cohort-level discussions of a condition to population-level analyses of sentiment, social media have provided scientists with unprecedented amounts of data to study human behavior associated with a variety of health conditions and medical treatments. Here we review recent work in mining social media for biomedical, epidemiological, and social phenomena information relevant to the multilevel complexity of human health. We pay particular attention to topics where social media data analysis has shown the most progress, including pharmacovigilance and sentiment analysis, especially for mental health. We also discuss a variety of innovative uses of social media data for health-related applications as well as important limitations of social media data access and use.
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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.