Overview
Covers state-of-art techniques and applications for harnessing social web in health research
Presents success stories of leveraging social web in health research
Illustrates in detail mainstream data mining techniques for analyzing social web data and their pros and cons
Discusses the limitations and potential biases of using social media data in health research and how to potentially mitigate these limitations
Reviews how behavioral interventions can be carried out using social web
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Table of contents (13 chapters)
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Front Matter
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Back Matter
Keywords
- social media health research
- social digital disease surveillance
- social media health education
- social media health professional
- Social media mental health
- social media health data
- Sentiment analysis social media
- mining social health status
- person attributes social media
- mining social media health
- vocabulary gap health professionals
- social media intervention studies
- social media cancer research
- Ethical social media health
- social media tobacco control
About this book
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.
Editors and Affiliations
About the editors
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.
Bibliographic Information
Book Title: Social Web and Health Research
Book Subtitle: Benefits, Limitations, and Best Practices
Editors: Jiang Bian, Yi Guo, Zhe He, Xia Hu
DOI: https://doi.org/10.1007/978-3-030-14714-3
Publisher: Springer Cham
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-14713-6Published: 11 July 2019
Softcover ISBN: 978-3-030-14716-7Published: 01 August 2020
eBook ISBN: 978-3-030-14714-3Published: 29 June 2019
Edition Number: 1
Number of Pages: XIII, 272
Number of Illustrations: 12 b/w illustrations, 19 illustrations in colour
Topics: Biomedical Engineering/Biotechnology, Health Informatics, Health Informatics, Biomedical Engineering and Bioengineering