Coverart for item
The Resource Dark web : exploring and data mining the dark side of the web, Hsinchun Chen

Dark web : exploring and data mining the dark side of the web, Hsinchun Chen

Label
Dark web : exploring and data mining the dark side of the web
Title
Dark web
Title remainder
exploring and data mining the dark side of the web
Statement of responsibility
Hsinchun Chen
Creator
Subject
Language
  • eng
  • eng
Summary
Annotation
Member of
Cataloging source
GW5XE
http://library.link/vocab/creatorName
Chen, Hsinchun
Dewey number
006.3/12
Government publication
federal national government publication
Index
index present
Language note
English
LC call number
QA76.9.D343
LC item number
C44 2012
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Integrated series in information systems,
Series volume
v. 30
http://library.link/vocab/subjectName
  • Data mining
  • Internet and terrorism
  • World Wide Web
  • Internet
  • COMPUTERS
  • Science économique
  • Affaires
  • Data mining
  • Internet
  • Internet and terrorism
  • World Wide Web
Summary expansion
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 to perform terrorism research and facilitate international security and peace. This monograph aims to provide an overview of the Dark Web landscape, suggest a systematic, computational approach to understanding the problems, and illustrate with selected techniques, methods, and case studies developed by the University of Arizona AI Lab Dark Web team members. This work aims to provide an interdisciplinary and understandable monograph about Dark Web research along three dimensions: methodological issues in Dark Web research; database and computational techniques to support information collection and data mining; and legal, social, privacy, and data confidentiality challenges and approaches. It will bring useful knowledge to scientists, security professionals, counterterrorism experts, and policy makers. The monographcan also serve as a reference material or textbook in graduate level courses related to information security, information policy, information assurance, information systems, terrorism, and public policy
Label
Dark web : exploring and data mining the dark side of the web, Hsinchun Chen
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Dark web research overview -- Intelligence and security informatics (ISI) : Research framework -- Terrorism informatics -- Forum spidering -- Link and content analysis -- Dark network analysis -- Interactional coherence analysis -- Dark web attribute system -- Authorship analysis -- Sentiment analysis -- Affect analysis -- CyberGate visualization -- Dark web forum portal -- Jihadi video analysis -- Extremist You Tube videos -- Improvised Explosive Devices (IED) on dark web -- Weapons of Mass Destruction (WMD) on dark web -- Bioterrorism knowledge mapping -- Women's forums on the dark web -- US domestic extremist groups -- International Falun Gong movement on the web -- Botnets and cyber criminals
Control code
769456536
Dimensions
unknown
Extent
1 online resource (xxvi, 451 pages)
Form of item
online
Isbn
9781461415565
Lccn
2011941611
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-1-4614-1557-2
http://library.link/vocab/ext/overdrive/overdriveId
146141556x
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)769456536
Label
Dark web : exploring and data mining the dark side of the web, Hsinchun Chen
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Dark web research overview -- Intelligence and security informatics (ISI) : Research framework -- Terrorism informatics -- Forum spidering -- Link and content analysis -- Dark network analysis -- Interactional coherence analysis -- Dark web attribute system -- Authorship analysis -- Sentiment analysis -- Affect analysis -- CyberGate visualization -- Dark web forum portal -- Jihadi video analysis -- Extremist You Tube videos -- Improvised Explosive Devices (IED) on dark web -- Weapons of Mass Destruction (WMD) on dark web -- Bioterrorism knowledge mapping -- Women's forums on the dark web -- US domestic extremist groups -- International Falun Gong movement on the web -- Botnets and cyber criminals
Control code
769456536
Dimensions
unknown
Extent
1 online resource (xxvi, 451 pages)
Form of item
online
Isbn
9781461415565
Lccn
2011941611
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-1-4614-1557-2
http://library.link/vocab/ext/overdrive/overdriveId
146141556x
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)769456536

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