Overview
- Proposes a new way of thinking about the emergence of online groups
- Presents a new method for measuring elite stability and group structuration through quantitative research on large, intact data sets
- Connects traditional sociological and communication literature with big data analysis
- Introduces real-time analytical strategies that may improve the way we manage online knowledge production systems
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Social Networks (LNSN)
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Table of contents (11 chapters)
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Structural Differentiation and Social Media: Theoretical Framework
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Configurational Change Phases and Motors in Online Collaboration
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Future Theoretical and Practical Directions
Keywords
About this book
This work fundamentally changes the way we think about social media leadership and evolution, emphasizing thecrucial contributions of leadership, of elite social roles, and of group global structure to the overall success and stability of large social media projects. Written in an accessible and direct style, the book will be of interest to academics as well as professionals with an interest in social media and commons-based peer production processes.
Authors and Affiliations
About the authors
Brian C. Britt, Assistant Pro
fessor, Department of Journalism and Mass Communication, South Dakota State University. Dr. Britt is a computational social scientist who focuses on the intersection between organizational communication and new media, with a particular emphasis on the strategies employed by individuals positioning themselves in online organizations. His work has been funded by the National Science Foundation and the National Institutes of Health and has resulted in several book chapters in edited volumes.
Bibliographic Information
Book Title: Structural Differentiation in Social Media
Book Subtitle: Adhocracy, Entropy, and the "1 % Effect"
Authors: Sorin Adam Matei, Brian C. Britt
Series Title: Lecture Notes in Social Networks
DOI: https://doi.org/10.1007/978-3-319-64425-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-64424-0Published: 21 September 2017
Softcover ISBN: 978-3-319-87791-4Published: 11 August 2018
eBook ISBN: 978-3-319-64425-7Published: 20 September 2017
Series ISSN: 2190-5428
Series E-ISSN: 2190-5436
Edition Number: 1
Number of Pages: XI, 247
Number of Illustrations: 1 b/w illustrations, 32 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Media Sociology, Social Media, Communication Studies, Big Data/Analytics, Applications of Graph Theory and Complex Networks