ArticleYearbook of medical informatics2019
Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data.
Article in Yearbook of medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.
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Who cites it
35 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis.Journal of medical Internet research · 2024Pooled it
- Pooled it
- Toward an Ethical Framework for the Text Mining of Social Media for Health Research: A Systematic Review.Frontiers in digital health · 2020Pooled it
- Rethinking Dengue Preparedness in the Era of Climate Change, Urbanisation, and Digital Health: A Structured Narrative Review.Medicina (Kaunas, Lithuania) · 2026Review
- Converging Representations of Attention-Deficit/Hyperactivity Disorder and Autism on Social Media: Linguistic and Topic Analysis of Trends in Reddit Data.Journal of medical Internet research · 2025Article
- Which social media platforms facilitate monitoring the opioid crisis?PLOS digital health · 2025Article
- Potential for advances in data linkage and data science to support injury prevention research.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2024Article
- The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review.JMIR infodemiology · 2024Article
- The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study.Journal of medical Internet research · 2024Article
- #Delta8: a retailer-driven increase in Delta-8 THC discussions on Twitter from 2020 to 2021.The American journal of drug and alcohol abuse · 2023Article
- #ChronicPain: Automated Building of a Chronic Pain Cohort from Twitter Using Machine Learning.Health data science · 2023Article
- Generalizable Natural Language Processing Framework for Migraine Reporting from Social Media.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Consumer-Generated Discourse on Cannabis as a Medicine: Scoping Review of Techniques.Journal of medical Internet research · 2022Article
- Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis.JMIR formative research · 2022Article
- Comparison of Pretraining Models and Strategies for Health-Related Social Media Text Classification.Healthcare (Basel, Switzerland) · 2022Article
- Assessing rigid modes of thinking in self-declared abortion ideology: natural language processing insights from an online pilot qualitative study on abortion attitudes.Pilot and feasibility studies · 2022Article
- Vaccine Adverse Event Mining of Twitter Conversations: 2-Phase Classification Study.JMIR medical informatics · 2022Article
- Article
- Monitoring COVID-19 pandemic through the lens of social media using natural language processing and machine learning.Health information science and systems · 2021Article
- Studies of Depression and Anxiety Using Reddit as a Data Source: Scoping Review.JMIR mental health · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
objectiveWe present a narrative review of recent work on the utilisation of Natural Language Processing (NLP) for the analysis of social media (including online health communities) specifically for public health applications.
methodsWe conducted a literature review of NLP research that utilised social media or online consumer-generated text for public health applications, focussing on the years 2016 to 2018. Papers were identified in several ways, including PubMed searches and the inspection of recent conference proceedings from the Association of Computational Linguistics (ACL), the Conference on Human Factors in Computing Systems (CHI), and the International AAAI (Association for the Advancement of Artificial Intelligence) Conference on Web and Social Media (ICWSM). Popular data sources included Twitter, Reddit, various online health communities, and Facebook.
resultsIn the recent past, communicable diseases (e.g., influenza, dengue) have been the focus of much social media-based NLP health research. However, mental health and substance use and abuse (including the use of tobacco, alcohol, marijuana, and opioids) have been the subject of an increasing volume of research in the 2016 - 2018 period. Associated with this trend, the use of lexicon-based methods remains popular given the availability of psychologically validated lexical resources suitable for mental health and substance abuse research. Finally, we found that in the period under review "modern" machine learning methods (i.e. deep neural-network-based methods), while increasing in popularity, remain less widely used than "classical" machine learning methods.
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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.