Big Data in Computational Social Science and Humanities

  • Shu-Heng Chen

Part of the Computational Social Sciences book series (CSS)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Practice

  3. Survey and Challenges

    1. Front Matter
      Pages 233-233
    2. Dehua Shen, Shu-Heng Chen
      Pages 235-248
    3. Lee-Xieng Yang
      Pages 249-262
    4. David Blundell, Ching-Chih Lin, James X. Morris
      Pages 263-288
    5. Michael J. Gallagher
      Pages 289-296
    6. Michael D. Fischer, Carol R. Ember
      Pages 323-336
    7. Andrea Nanetti, Siew Ann Cheong
      Pages 337-363
  4. Back Matter
    Pages 379-388

About this book


This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. 

The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities.  The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? 

With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.


big data for social scientists agent-based computational economics computational humanities big data governance big data and cloud computing behavioral economics and big data big data and history

Editors and affiliations

  • Shu-Heng Chen
    • 1
  1. 1.AI-ECON Research Center, Department of EconomicsNational Chengchi UniversityTaipeiTaiwan

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-95464-6
  • Online ISBN 978-3-319-95465-3
  • Series Print ISSN 2509-9574
  • Series Online ISSN 2509-9582
  • Buy this book on publisher's site
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