Overview
- Contains for the first time in a single volume, chapters that take the reader from novice to expert on spreading processes in social systems
- Uniquely emphasizes a data-driven approach to the problem of complex contagion
- Includes numerous chapters on spreading in systems ranging from online social networks to large-scale measurements of face-to-face interactions
Part of the book series: Computational Social Sciences (CSS)
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Table of contents (19 chapters)
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Front Matter
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Introduction to Spreading in Social Systems
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Front Matter
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Models and Theories
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Front Matter
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Observational Studies
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Front Matter
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Controlled Studies
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Front Matter
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Keywords
About this book
This text is about spreading of information and influence in complex networks. Although previously considered similar and modeled in parallel approaches, there is now experimental evidence that epidemic and social spreading work in subtly different ways. While previously explored through modeling, there is currently an explosion of work on revealing the mechanisms underlying complex contagion based on big data and data-driven approaches.
This volume consists of four parts. Part 1 is an Introduction, providing an accessible summary of the state of the art. Part 2 provides an overview of the central theoretical developments in the field. Part 3 describes the empirical work on observing spreading processes in real-world networks. Finally, Part 4 goes into detail with recent and exciting new developments: dedicated studies designed to measure specific aspects of the spreading processes, often using randomized control trials to isolate the network effect from confounders, such as homophily.
Each contribution is authored by leading experts in the field. This volume, though based on technical selections of the most important results on complex spreading, remains quite accessible to the newly interested. The main benefit to the reader is that the topics are carefully structured to take the novice to the level of expert on the topic of social spreading processes. This book will be of great importance to a wide field: from researchers in physics, computer science, and sociology to professionals in public policy and public health.
Editors and Affiliations
About the editors
Yong-Yeol (YY) Ahn is an assistant professor at Indiana University School of Informatics, Computing, and Engineering. He worked as a postdoctoral research associate at the Center for Complex Network Research at Northeastern University and as a visiting researcher at the Center for Cancer Systems Biology at Dana-Farber Cancer Institute after earning his PhD in Statistical Physics from KAIST in 2008. He has made contributions in a variety of areas including the study of network community structure, information diffusion, and culture. He is a recipient of several awards, including the Microsoft Research Faculty Fellowship and the LinkedIn Economic Graph Challenge.
Bibliographic Information
Book Title: Complex Spreading Phenomena in Social Systems
Book Subtitle: Influence and Contagion in Real-World Social Networks
Editors: Sune Lehmann, Yong-Yeol Ahn
Series Title: Computational Social Sciences
DOI: https://doi.org/10.1007/978-3-319-77332-2
Publisher: Springer Cham
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-77331-5Published: 09 July 2018
Softcover ISBN: 978-3-030-08430-1Published: 10 January 2019
eBook ISBN: 978-3-319-77332-2Published: 21 June 2018
Series ISSN: 2509-9574
Series E-ISSN: 2509-9582
Edition Number: 1
Number of Pages: VI, 361
Number of Illustrations: 23 b/w illustrations, 81 illustrations in colour
Topics: Applications of Graph Theory and Complex Networks, Data Mining and Knowledge Discovery, Methodology of the Social Sciences, Simulation and Modeling