Big Data Is Not a Monolith
eBook - ePub

Big Data Is Not a Monolith

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

About this book

Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies.

The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, "data harm," and decision making.

Contributors
Ryan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West

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Yes, you can access Big Data Is Not a Monolith by Cassidy R. Sugimoto,Hamid R. Ekbia,Michael Mattioli, Sandra Braman in PDF and/or ePUB format, as well as other popular books in Languages & Linguistics & Data Mining. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Series page
  3. Title page
  4. Copyright page
  5. Table of Contents
  6. Series Editor’s Introduction
  7. Acknowledgments
  8. Introduction
  9. Iā€ƒBig Data and Individuals
  10. IIā€ƒBig Data and Society
  11. IIIā€ƒBig Data and Science
  12. IVā€ƒBig Data and Organizations
  13. References
  14. Contributors
  15. Index