Big Data Factories Collaborative Approaches
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
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Sorin Adam Matei Nicolas Jullien Sean P. Goggins Editors
Big Data Factories Collaborative 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 Goncalves 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
Sorin Adam Matei • Nicolas Jullien Sean P. Goggins Editors
Big Data Factories Collaborative Approaches
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Editors Sorin Adam Matei Purdue University West Lafayette IN, USA
Nicolas Jullien Technopôle Brest-Iroise IMT Atlantique (Telecom Bretagne) Brest Cedex 3, France
Sean P. Goggins Computer Science University of Missouri Columbia, MO, USA
ISSN 2509-9574 ISSN 2509-9582 (electronic) Com
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