EgoClustering: Overlapping Community Detection via Merged Friendship-Groups
There has been considerable interest in identifying communities within large collections of social networking data. Existing algorithms will classify an actor (node) into a single group, ignoring the fact that in real-world situations people tend to belon
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Tansel Özyer · Jon Rokne Gerhard Wagner · Arno H.P. Reuser Editors
The Influence of Technology on Social Network Analysis and Mining
The Influence of Technology on Social Network Analysis and Mining
Lecture Notes in Social Networks (LNSN)
Series Editors Reda Alhajj University of Calgary Calgary, AB, Canada
Uwe Glässer Simon Fraser University Burnaby, BC, Canada
Advisory Board Charu Aggarwal, IBM T.J. Watson Research Center, Hawthorne, NY, USA Patricia L. Brantingham, Simon Fraser University, Burnaby, BC, Canada Thilo Gross, University of Bristol, United Kingdom Jiawei Han, University of Illinois at Urbana-Champaign, IL, USA Huan Liu, Arizona State University, Tempe, AZ, USA Raúl Manásevich, University of Chile, Santiago, Chile Anthony J. Masys, Centre for Security Science, Ottawa, ON, Canada Carlo Morselli, University of Montreal, QC, Canada Rafael Wittek, University of Groningen, The Netherlands Daniel Zeng, The University of Arizona, Tucson, AZ, USA
For further volumes: www.springer.com/series/8768
Tansel Özyer Jon Rokne Gerhard Wagner Arno H.P. Reuser Editors
The Influence of Technology on Social Network Analysis and Mining
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Editors Tansel Özyer Department of Computer Engineering TOBB University Sogutozu Ankara Turkey Jon Rokne Department of Computer Science University of Calgary Calgary Canada
Gerhard Wagner IPSC European Commission Joint Research Centre Ispra Italy Arno H.P. Reuser Leiden Netherlands
This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically those of translation, reprinting, re-use of illustrations, broadcasting, reproduction by photocopying machines or similar means, and storage in data banks. Product Liability: The publisher can give no guarantee for all the information contained in this book. The use of registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. c 2013 Springer-Verlag/Wien SpringerWienNewYork is a part of Springer Science+Business Media springer.at Typesetting: SPi, Pondicherry, India Printed on acid-free and chlorine-free bleached paper SPIN: 86130600 With 216 Figures Library of Congress Control Number: 2013933244 ISBN 978-3-7091-1345-5 e-ISBN 978-3-7091-1346-2 DOI 10.1007/978-3-7091-1346-2 SpringerWienNewYork
Preface
This edited book contains extended versions of selected papers from ASONAM 2010 which was held at the University of Odense, Denmark, August 9–11, 2010. From the many excellent papers submitted to the conference, 28 were chosen for this volume. The volume explores a number of aspects of social networks, both global and local, and it also shows how social networks analysis and mining may aid web searches, product acceptances and personalized recommendations just to mention a few areas where social networks analysis can improve results in other mostly web-related areas. The application of graph theoreti
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