Springer Social Web and Health Research: Benefits, Limitations, and Best Practices

This book presents state-of-the-art research methods, results, and applications in social media and health research. It aims to help readers better understand the different aspects of using social web platforms in health research. Throughout the chapters, the benefits, limitations, and best practices of using a variety of social web platforms in health research are discussed with concrete use cases. This is an ideal book for biomedical researchers, clinicians, and health consumers (including patients) who are interested in learning how social web platforms impact health and healthcare research. From the Back Cover This book presents state-of-the-art research methods, results, and applications in social media and health research. It aims to help readers better understand the different aspects of using social web platforms in health research. Throughout the chapters, the benefits, limitations, and best practices of using a variety of social web platforms in health research are discussed with concrete use cases. This is an ideal book for biomedical researchers, clinicians, and health consumers (including patients) who are interested in learning how social web platforms impact health and healthcare research. About the Author Jiang Bian  Dr. Bian is an Assistant Professor of Biomedical Informatics in the Department of Health Outcomes and Biomedical Informatics at the University of Florida.  He is also the Director of Cancer Informatics and eHealth Core for the University of Florida Health Cancer Center.  He has a diverse yet strong multi-disciplinary background and extensive expertise in social media analysis, machine learning, natural language processing, network science, ontology development and evaluation, semantic web technology and software engineering.  Yi Guo  Dr. Yi Guo is an Assistant Professor in the Department of Health Outcomes and Biomedical Informatics in the College of Medicine at University of Florida.  He is a health outcomes researcher and data scientist with expertise in data integration and discovery, multilevel and longitudinal models, health risk prediction models, quality measurement and psychometric analysis, and power and sample size analysis. Zhe He  Dr. Zhe He is an Assistant Professor in the School of Information at the Florida State University. He is an Associate Editor of BMC Medical Informatics and Decision Making. His research lies in biomedical and health informatics, clinical research informatics, knowledge discovery, knowledge representation, and ontology-enhanced data analytics. His research aims to improve the population health and advance biomedical research through the collection, analysis, and application of electronic health data from heterogeneous sources. Xia Hu  Dr. Xia "Ben" Hu is currently a tenure-track Assistant Professor at Texas A&M University in the Department of Computer Science and Engineering. Dr. Hu has published nearly 100 papers in several major academic venues, including WWW, SIGIR, KDD, ICDM, SDM, WSDM, IJCAI, AAAI, CIKM, ICWSM, etc. His work on deep collaborative filtering, anomaly detection and knowledge graph have been included in the TensorFlow package, Apple production system and Bing production system, respectively.