Big Data Factories: Collaborative Approaches (Computational Social Sciences). This item is unavailable.
Language: English
Published by Springer, 2017
- Hardcover
- New

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Seller Inventory # ria9783319591858_new
- Title
- Big Data Factories: Collaborative Approaches (Computational Social Sciences)
- Publisher
- Springer
- Publication year
- 2017
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319591851
- ISBN 13
- 9783319591858
- Item weight
- 508 grams
- Series
- Book 12 of 26: Computational Social Sciences
The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as “data factoring” emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing.
Finally, the book presents the teaching utility of data factoring and the ethical and privacy concerns related to it.
Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com
"Synopsis" may belong to another edition of this title.
About the Author
Sorin Matei is a Professor at Brian Lamb School of Communication at Purdue University. His focus areas are computational social science, collaborative content production, and data storytelling.
Nicolas Jullien is an Associate Professor at the LUSSI Department of Telecom Bretagne. His research interests are in open and online communities.
Sean Patrick Goggins is an Associate Professor at Missouri's iSchool, with courtesy appointments as core faculty in the University of Missouri's Informatics Institute and Department of Computer Science.
"About the title" may belong to another edition of this title.