Social Phenomena From Data Analysis to Models
This book focuses on the new possibilities and approaches to social modeling currently being made possible by an unprecedented variety of datasets generated by our interactions with modern technologies. This area has witnessed a veritable explosion of act
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Bruno Gonçalves Nicola Perra Editors
Social Phenomena From Data Analysis to Models
Computational Social Sciences A series of authored and edited monographs that utilize quantitative and computational methods to model, analyze, and interpret large-scale social phenomena. Titles within the series contain methods and practices that test and develop theories of complex social processes through bottom-up modeling of social interactions. Of particular interest is the study of the co-evolution of modern communication technology and social behavior and norms, in connection with emerging issues such as trust, risk, security, and privacy in novel socio-technical environments. Computational Social Sciences is explicitly transdisciplinary: quantitative methods from fields such as dynamical systems, artificial intelligence, network theory, agent-based modeling, and statistical mechanics are invoked and combined with state-of-the-art mining and analysis of large data sets to help us understand social agents, their interactions on and offline, and the effect of these interactions at the macro level. Topics include, but are not limited to social networks and media, dynamics of opinions, cultures and conflicts, socio-technical co-evolution, and social psychology. Computational Social Sciences will also publish monographs and selected edited contributions from specialized conferences and workshops specifically aimed at communicating new findings to a large transdisciplinary audience. A fundamental goal of the series is to provide a single forum within which commonalities and differences in the workings of this field may be discerned, hence leading to deeper insight and understanding. Series Editors Elisa Bertino Purdue University, West Lafayette, IN, USA
Larry Liebovitch Queens College, City University of New York, Flushing, NY, USA
Jacob Foster University of California, Los Angeles, CA, USA
Sorin A. Matei Purdue University, West Lafayette, IN, USA
Nigel Gilbert University of Surrey, Guildford, UK Jennifer Golbeck University of Maryland, College Park, MD, USA James A. Kitts University of Massachusetts, Amherst, MA, USA
Anton Nijholt University of Twente, Enschede, The Netherlands Robert Savit University of Michigan, Ann Arbor, MI, USA Alessandro Vinciarelli University of Glasgow, Scotland
More information about this series at http://www.springer.com/series/11784
Bruno Gonçalves • Nicola Perra Editors
Social Phenomena From Data Analysis to Models
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Editors Bruno Gonçalves Centre de Physique Théorique Aix-Marseille Université Campus de Luminy, Case 907 Marseille, France
Computational Social Sciences ISBN 978-3-319-14010-0 DOI 10.1007/978-3-319-14011-7
Nicola Perra MoBS Lab Northeastern University Boston, MA, USA
ISBN 978-3-319-14011-7 (eBook)
Library of Congress Control Number: 2015939174 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is con
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