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Applications of Data-Centric Science to Social Design

Qualitative and Quantitative Understanding of Collective Human Behavior

  • Aki-Hiro Sato
Book

Part of the Agent-Based Social Systems book series (ABSS, volume 14)

Table of contents

  1. Front Matter
    Pages i-x
  2. Methods for Data Analysis and Design

  3. Mathematical Foundation of Human Collective Behavior

    1. Front Matter
      Pages 63-63
    2. Masato Hisakado, Shintaro Mori
      Pages 65-79
    3. Masato Hisakado, Shintaro Mori
      Pages 99-118
    4. Masato Hisakado, Shintaro Mori
      Pages 119-139
    5. Shintaro Mori, Masato Hisakado
      Pages 141-165
    6. Shintaro Mori, Masato Hisakado
      Pages 167-179
    7. Shintaro Mori, Masato Hisakado
      Pages 181-191
    8. Masato Hisakado, Shintaro Mori
      Pages 193-202
  4. Applications of Data Analysis to Social Design

About this book

Introduction

The intention behind this book is to illustrate the deep relation among human behavior, data-centric science, and social design. In fact, these three issues have been independently developing in different fields, although they are, of course, deeply interrelated to one another. Specifically, fundamental understanding of human behavior should be employed for investigating our human society and designing social systems. Insights and both quantitative and qualitative understandings of collective human behavior are quite useful when social systems are designed. 
Fundamental principles of human behavior, theoretical models of human behavior, and information cascades are addressed as aspects of human behavior. Data-driven investigation of human nature, social behavior, and societal systems are developed as aspects of data-centric science. As design aspects, how to design social systems from heterogeneous memberships is explained. There is also discussion of these three aspects—human behavior, data-centric science, and social design—independently and with regard to the relationships among them.

Keywords

Collective Human Behavior Big Data Data-driven Innovation Phase Transition Benefits of Inconvenience Information Cascade

Editors and affiliations

  • Aki-Hiro Sato
    • 1
  1. 1.Yokohama City UniversityKanazawa-ku, Yokohama-shiJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-7194-2
  • Copyright Information Springer Nature Singapore Pte Ltd. 2019
  • Publisher Name Springer, Singapore
  • eBook Packages Business and Management
  • Print ISBN 978-981-10-7193-5
  • Online ISBN 978-981-10-7194-2
  • Series Print ISSN 1861-0803
  • Buy this book on publisher's site
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