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Author:   Katharina A. Zweig
Publisher:   Springer Verlag GmbH
Imprint:   Springer Verlag GmbH
Edition:   1st ed. 2016
Dimensions:   Width: 15.50cm , Height: 3.40cm , Length: 23.50cm
Weight:   1.252kg
ISBN:  

9783709107409

ISBN 10:   3709107407
Pages:   535
Publication Date:   27 October 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Dedication.- Preface.- Part I Introduction.- A First Encounter.- Graph Theory, Social Network Analysis, and Network Science.- Definitions.- Part II Methods.- Classic Network Analytic Measures.- Network Representations of Complex Systems.- Random Graphs and Network Models.- Random Graphs as Null Models.- Understanding and Designing Network Measures.- Centrality Indices.- Part III Literacy.- Literacy: Data Quality, Entities and Nodes.- Literacy: Relationships and Relations.- Literacy: When is a Network Model Explanatory?.- Literacy: Choosing the Best Null Model.- Literacy Interpretation.- Ethics in Network Analysis.- Appendix A - The structure and typical outlets of network analytic papers.- Appendix B - Glossary.- Appendix C - Solutions to the Problems.- Name Index.- Subject Index.

Reviews

“The book is a good source for researchers, network experts, and scientists studying network analytics. … It can also be used as a textbook in graduate classes. There are exercises and further reading sections at the end of each chapter, which will be useful to instructors. The book will also help readers understand how to think in a network analytics discipline.” (Gulustan Dogan, Computing Reviews, February, 2018)​

The book is a good source for researchers, network experts, and scientists studying network analytics. ... It can also be used as a textbook in graduate classes. There are exercises and further reading sections at the end of each chapter, which will be useful to instructors. The book will also help readers understand how to think in a network analytics discipline. (Gulustan Dogan, Computing Reviews, February, 2018)

Author Information

Katharina A. Zweig has studied biochemistry and bioinformatics at the University Tübingen, Germany (1996-2006). In her doctoral studies, she was concerned with the relation of local structure and global behavior in the evolution of complex networks (2007, University Tübingen, Germany). Her postdoc was done in statistical physics at ELTE University, Hungary (2008-09); after that she lead an independent junior research group at University Heidelberg, Germany (2009-2012). Since 2012, she is a professor for „Graph Theory and Complex Network Analysis“ at TU Kaiserslautern, Germany. She is a Junior Fellow of the German Society of Computer Science and was elected as one of 39 Digital Thinkers („Digitale Köpfe“) in 2014 in Germany. Since she started to work on the use of centrality indices in network analysis in 2003, network analysis literacy has been her main concern. Currently, her research is focused on the more general question of how to make algorithms accountable, i.e., how to make surethat an algorithm’s numerical answer matches the intuition behind the problem modeled by it. In 2016, she co-founded Algorithm Watch, a non-profit organisation to hold algorithms accountable and to consult society, politics, industry and public institutions about all questions concerning algorithm accountability.

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