Applications of Data Centric Science to Social Design is popular PDF and ePub book, written by Aki-Hiro Sato in 2019, it is a fantastic choice for those who relish reading online the Knowledge management genre. Let's immerse ourselves in this engaging Knowledge management book by exploring the summary and details provided below. Remember, Applications of Data Centric Science to Social Design can be Read Online from any device for your convenience.

Applications of Data Centric Science to Social Design Book PDF Summary

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.

Detail Book of Applications of Data Centric Science to Social Design PDF

Applications of Data Centric Science to Social Design
  • Author : Aki-Hiro Sato
  • Release : 28 September 2024
  • Publisher : Unknown
  • ISBN : 9811071950
  • Genre : Knowledge management
  • Total Page : 266 pages
  • Language : English
  • PDF File Size : 16,7 Mb

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Human Centered Data Science

Human Centered Data Science Author : Cecilia Aragon,Shion Guha,Marina Kogan,Michael Muller,Gina Neff
Publisher : MIT Press
File Size : 8,7 Mb
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