Health Web Science: Social Media Data for Healthcare [Hardcover]

This book introduces the field of Health Web Science and presents methods for information gathering from written social media data. It explores the availability and utility of the personal medical information shared on social media platforms and determines ways to apply this largely untapped information source to healthcare systems and public health monitoring. Introducing an innovative concept for integrating social media data with clinical data, it addresses the crucial aspect of combining experiential data from social media with clinical evidence, and explores how the variety of available social media content can be analyzed and implemented. The book tackles a range of topics including social medias role in healthcare, the gathering of shared information, and the integration of clinical and social media data. Application examples of social media for health monitoring, along with its usage in patient treatment are also provided. The book also considers the ethical and legal issues of gathering and utilizing social media data, along with the risks and challenges that must be considered when integrating social media data into healthcare choices. With an increased interest internationally in E-Health, Health 2.0, Medicine 2.0 and the recent birth of the discipline of Web Science, this book will be a valuable resource for researchers and practitioners investigating this emerging topic.

The Medical Web and Its Authors.- Applications of Social Media in Healthcare.- Objectives and Structure of the Book.- Types of Medical Social Media.- Excursus: Content and Language in Clinical Narratives.- Content and Language in Medical Social Media.- Text analytic-Enabled Healthcare Applications: Requirements and Architecture.- Information Extraction from Medical Social Media.- Relation Extraction.- Sentiment Analysis from Medical Texts.- Social Media for Health Monitoring.- Diversity-aware Search.- Implementation obstacles.- Ethics in Health Web Science.- Integrating Clinical32