Dark Web Exploring and Data Mining the Dark Side of the Web
The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach. We ai
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Series Editors Ramesh Sharda Oklahoma State University, Stillwater, OK, USA Stefan Voß University of Hamburg, Hamburg, Germany
For further volumes: http://www.springer.com/series/6157
Hsinchun Chen
Dark Web Exploring and Data Mining the Dark Side of the Web
Hsinchun Chen Department of Management Information Systems University of Arizona Tuscon, AZ, USA [email protected]
ISSN 1571-0270 ISBN 978-1-4614-1556-5 e-ISBN 978-1-4614-1557-2 DOI 10.1007/978-1-4614-1557-2 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011941611 © Springer Science+Business Media, LLC 2012 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
Aims The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (jihadist) phenomena via a computational, data-centric approach. We aim to collect “ALL” web content generated by international terrorist groups, including web sites, forums, chat rooms, blogs, social networking sites, videos, virtual world, etc. We have developed various multilingual data mining, text mining, and web mining techniques to perform link analysis, content analysis,web metrics (technical sophistication) analysis, sentiment analysis, authorship analysis, and video analysis in our research. The approaches and methods developed in this project contribute to advancing the field of Intelligence and Security Informatics (ISI). Such advances will help related stakeholders perform terrorism research and facilitate international security and peace. Dark Web research has been featured in many national, international and local press and media, including: National Science Foundation press, Associated Press, BBC, Fox News, National Public Radio, Science News, Discover Magazine, Information Outlook, Wired Magazine, The Bulletin (Australian), Australian Broadcasting Corporation, Arizona Daily Star, East Valley Tribune, Phoenix ABC Channel 15, and Tucson Channels 4, 6, and 9. As an NSF-funded research project, our research team has generated significant findings and publications in major computer science and information systems journals and conferences. We hope our research will help educate the next gener
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