Harness social media data to improve population health and reduce disparities

From Posts to Patterns solves an urgent problem in public health research: the underutilization of social media as a data source. With adults spending 2.5 hours daily on social platforms, social media is a pervasive exposure that influences how people communicate, the information they receive, and their interactions and behaviors both online and offline. In this book, leading social epidemiologists provide practical guidance for leveraging social media data to address health disparities.

The book delivers a comprehensive roadmap for collecting, cleaning, and analyzing social media data in accessible language. It explores measuring cultural racism, investigating underground health behaviors, and deploying social media interventions. The authors present evidence-based strategies for reducing health disparities and improving population health.

 Readers will also find:

• Practical tools and methods for collecting, cleaning, and analyzing social media data for health research, accessible to users with and without advanced technical skills

• Evidence-based frameworks for measuring area-level racial bias and tracking temporal and geographic changes in health-related discourse across populations

• Strategies for investigating illicit or underground health behaviors through social platforms that traditional research methods cannot easily capture

• Guidance on understanding both the benefits and harms of social media, including its role in spreading misinformation, building communities, and enabling health activism

• Real-world case studies demonstrating how social media data provides near real-time insights into emerging diseases, behaviors, and therapies with greater geographic and temporal granularity than traditional studies

From Posts to Patterns is essential for public health researchers expanding their methodological toolkit, policy makers reducing health disparities, and anyone understanding how digital environments shape health outcomes. This book empowers readers to harness social media’s potential for advancing health equity while navigating its challenges.

THU T. NGUYEN is Associate Professor of Epidemiology and Biostatistics at the University of Maryland School of Public Health and uses social media data and AI to study population health and health equity.

QUYNH C. NGUYEN is an investigator at the National Institute of Nursing Research, NIH, and Director of the HashtagHealth Lab, using social media, imagery, and AI to study health and health disparities.

SHANIECE CRISS is Associate Professor of Health Sciences and Director of the Masters of Arts in Advocacy and Social Policy at Furman University and examines how communication, leadership, and civic engagement shape community health.

YULIN HSWEN is Associate Professor at the University of Maryland and uses AI and digital data to uncover insights into human behavior, disease, and population health.