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Open Source Intelligence and Cyber Crime: Social Media Analytics 2020 ed. [Hardback]

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  • Formāts: Hardback, 251 pages, height x width: 235x155 mm, weight: 559 g, 69 Illustrations, color; 19 Illustrations, black and white; V, 251 p. 88 illus., 69 illus. in color., 1 Hardback
  • Sērija : Lecture Notes in Social Networks
  • Izdošanas datums: 01-Aug-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030412504
  • ISBN-13: 9783030412500
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  • Hardback
  • Cena: 100,46 €*
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  • Formāts: Hardback, 251 pages, height x width: 235x155 mm, weight: 559 g, 69 Illustrations, color; 19 Illustrations, black and white; V, 251 p. 88 illus., 69 illus. in color., 1 Hardback
  • Sērija : Lecture Notes in Social Networks
  • Izdošanas datums: 01-Aug-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030412504
  • ISBN-13: 9783030412500
Citas grāmatas par šo tēmu:
This book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics.





 Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Protecting the Web from Misinformation
1(28)
Francesca Spezzano
Indhumathi Gurunathan
Studying the Weaponization of Social Media: Case Studies of Anti-NATO Disinformation Campaigns
29(24)
Katrin Galeano
Rick Galeano
Samer Al-Khateeb
Nitin Agarwal
You Are Known by Your Friends: Leveraging Network Metrics for Bot Detection in Twitter
53(36)
David M. Beskow
Kathleen M. Carley
Beyond the `Silk Road': Assessing Illicit Drug Marketplaces on the Public Web
89(24)
Richard Frank
Alexander Mikhaylov
Inferring Systemic Nets with Applications to Islamist Forums
113(28)
David B. Skillicorn
N. Alsadhan
Twitter Bots and the Swedish Election
141(24)
Johan Fernquist
Lisa Kaati
Ralph Schroeder
Nazar Akrami
Katie Cohen
Cognitively-Inspired Inference for Mai ware Task Identification
165(30)
Eric Nunes
Casey Buto
Paulo Shakarian
Christian Lebiere
Stefano Bennati
Robert Thomson
Social Media for Mental Health: Data, Methods, and Findings
195(26)
Nur Shazwanr Kamarudin
Ghazaleh Beigi
Lydia Manikonda
Huan Liu
Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study
221
Stefan Varga
Joel Brynielsson
Andreas Horndahl
Magnus Rosell