# Mining social media data for biomedical signals and health-related behavior

arXiv: https://arxiv.org/abs/2001.10285 · HTML: https://mlsanity.com/paper/2001.10285/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jan 2020.

## Built on by (most cited first, 7 of 7)

- [Claim Detection in Biomedical Twitter Posts](https://mlsanity.com/paper/2104.11639/) (2021)
- [Evaluating Large Language Models for Health-Related Text Classification Tasks with Public Social Media Data](https://mlsanity.com/paper/2403.19031/) (2024)
- [An Ensemble Classification Approach in A Multi-Layered Large Language Model Framework for Disease Prediction](https://mlsanity.com/paper/2509.02446/) (2025)
- [Mental Disorders on Online Social Media Through the Lens of Language and Behaviour: Analysis and Visualisation](https://mlsanity.com/paper/2202.03291/) (2022)
- [Social Behavior and Mental Health: A Snapshot Survey under COVID-19 Pandemic](https://mlsanity.com/paper/2105.08165/) (2021)
- [Refinement of an Epilepsy Dictionary through Human Annotation of Health-related posts on Instagram](https://mlsanity.com/paper/2405.08784/) (2024)
- [Identifying and Aligning Medical Claims Made on Social Media with Medical Evidence](https://mlsanity.com/paper/2405.11219/) (2024)

## Abstract (arXiv)

Social media data has been increasingly used to study biomedical and health-related phenomena. From cohort level discussions of a condition to planetary level analyses of sentiment, social media has provided scientists with unprecedented amounts of data to study human behavior and response 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, sentiment analysis especially for mental health, and other areas. We also discuss a variety of innovative uses of social media data for health-related applications and important limitations in social media data access and use.