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  • © 2019

Social Web and Health Research

Benefits, Limitations, and Best Practices

Editors:

  • 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)

  1. Front Matter

    Pages i-xiii
  2. Social Media in Health Communication

    • Jinhai Huo, Kea Turner
    Pages 53-82
  3. Learning Wellness Profiles of Users on Social Networks: The Case of Diabetes

    • Mohammad Akbari, Xia Hu, Tat-Seng Chua
    Pages 139-169
  4. Social Media and Psychological Disorder

    • Nur Hafieza Ismail, Mengnan Du, Xia Hu
    Pages 171-192
  5. Analysis by Multiclass Multilabel Classification of the 2015 #SmearForSmear Campaign Using Deep Learning

    • Yves Mercadier, Bilel Moulahi, Sandra Bringay, Jérôme Azé, Philippe Lenoir, Grégoire Mercier et al.
    Pages 193-205
  6. How to Improve Public Health via Mining Social Media Platforms: A Case Study of Human Papillomaviruses (HPV)

    • Hansi Zhang, Christopher Wheldon, Cui Tao, Adam G. Dunn, Yi Guo, Jinhai Huo et al.
    Pages 207-231
  7. Learning Hormonal Therapy Medication Adherence from an Online Breast Cancer Forum

    • Zhijun Yin, Jeremy Warner, Lijun Song, Pei-Yun Hsueh, Ching-Hua Chen, Bradley Malin
    Pages 233-257
  8. Ethics in Health Research Using Social Media

    • Rupa Valdez, Jessica Keim-Malpass
    Pages 259-269
  9. Back Matter

    Pages 271-272

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

  • Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, USA

    Jiang Bian, Yi Guo

  • School of Information, Florida State University, Tallahassee, USA

    Zhe He

  • Computer Science and Engineering Department, Texas A&M University, College Station, USA

    Xia Hu

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

Buy it now

Buying options

eBook USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access