Overview
- Provides a comprehensive overview of the use of big data in various disciplines of the social sciences and humanities
- Includes self-contained and easy-accessible chapters for big data governance
- Exemplifies the new kind of interdisciplinary collaborations in the big-data era
- Shows how the digital society brings in methodological innovations to social sciences and humanities
Part of the book series: Computational Social Sciences (CSS)
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Table of contents (19 chapters)
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Practice
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Survey and Challenges
Keywords
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.
Editors and Affiliations
About the editor
Bibliographic Information
Book Title: Big Data in Computational Social Science and Humanities
Editors: Shu-Heng Chen
Series Title: Computational Social Sciences
DOI: https://doi.org/10.1007/978-3-319-95465-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-95464-6Published: 29 November 2018
eBook ISBN: 978-3-319-95465-3Published: 21 November 2018
Series ISSN: 2509-9574
Series E-ISSN: 2509-9582
Edition Number: 1
Number of Pages: XIII, 388
Number of Illustrations: 12 b/w illustrations, 114 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Behavioral/Experimental Economics, Big Data/Analytics, Natural Language Processing (NLP), Philosophy of Technology, Political Science