Diffusion in Social Networks
This book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), socio
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Paulo Shakarian Abhinav Bhatnagar Ashkan Aleali Elham Shaabani Ruocheng Guo
Diffusion in Social Networks
123
SpringerBriefs in Computer Science
Series Editors Stan Zdonik Shashi Shekhar Jonathan Katz Xindong Wu Lakhmi C. Jain David Padua Xuemin (Sherman) Shen Borko Furht V.S. Subrahmanian Martial Hebert Katsushi Ikeuchi Bruno Siciliano Sushil Jajodia Newton Lee
More information about this series at http://www.springer.com/series/10028
Paulo Shakarian • Abhinav Bhatnagar Ashkan Aleali • Elham Shaabani Ruocheng Guo
Diffusion in Social Networks
123
Paulo Shakarian School of Computing, Informatics and Decision Systems Engineering Arizona State University Tempe, AZ, USA Ashkan Aleali Arizona State University Tempe, AZ, USA
Abhinav Bhatnagar Arizona State University Tempe, AZ, USA Elham Shaabani Arizona State University Tempe, AZ, USA
Ruocheng Guo Arizona State University Tempe, AZ, USA
ISSN 2191-5768 ISSN 2191-5776 (electronic) SpringerBriefs in Computer Science ISBN 978-3-319-23104-4 ISBN 978-3-319-23105-1 (eBook) DOI 10.1007/978-3-319-23105-1 Library of Congress Control Number: 2015947765 Springer Cham Heidelberg New York Dordrecht London © The Author(s) 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www. springer.com)
Preface
In recent years, research on diffusion process in social networks has grown in a variety of fields including computer science, physics, and biology. However, often times research in these individual disciplines becomes stove-piped. In this book, we focus on cutting-edge research in social network diffusion bringing together a range of ideas from these disciplines with the goal of creating a single volume that examines these ideas. We sought to cover many of the most important concepts, models, and methods from these areas. We felt by exploring a variety of work from different fields that we could help open the doo
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