Group Processes Data-Driven Computational Approaches
This volume introduces a series of different data-driven computational methods for analyzing group processes through didactic and tutorial-based examples. Group processes are of central importance to many sectors of society, including government, the mili
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Andrew Pilny Marshall Scott Poole Editors
Group Processes
Data-Driven Computational Approaches
Computational Social Sciences
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 Claudio Cioffi-Revilla George Mason University, Fairfax, VA, USA Jacob Foster University of California, Los Angeles, CA, USA Nigel Gilbert University of Surrey, Guildford, UK Jennifer Golbeck University of Maryland, College Park, MD, USA Bruno Gonçalves New York University, New York, NY, USA James A. Kitts Columbia University, Amherst, MA, USA
Larry Liebovitch Queens College, City University of New York, Flushing, NY, USA Sorin A. Matei Purdue University, West Lafayette, IN, USA Anton Nijholt University of Twente, Enschede, The Netherlands Andrzej Nowak University of Warsaw, Warsaw, Poland Robert Savit University of Michigan, Ann Arbor, MI, USA Flaminio Squazzoni University of Brescia, Brescia, Italy Alessandro Vinciarelli University of Glasgow, Glasgow, Scotland, UK
More information about this series at http://www.springer.com/series/11784
Andrew Pilny • Marshall Scott Poole Editors
Group Processes Data-Driven Computational Approaches
Editors Andrew Pilny University of Kentucky Lexington, KY, USA
Marshall Scott Poole University of Illinois Urbana, IL, USA
ISSN 2509-9574 ISSN 2509-9582 (electronic) Computational Social Sciences ISBN 978-3-319-48940-7 ISBN 978-3-319-48941-4 (eBook) DOI 10.1007/978-3-319-48941-4 Libr
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