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

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  • Formāts: Paperback / softback, 251 pages, height x width: 235x155 mm, weight: 403 g, 69 Illustrations, color; 19 Illustrations, black and white; V, 251 p. 88 illus., 69 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Social Networks
  • Izdošanas datums: 02-Aug-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030412539
  • ISBN-13: 9783030412531
Citas grāmatas par šo tēmu:
  • Mīkstie vāki
  • Cena: 73,68 €*
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  • Formāts: Paperback / softback, 251 pages, height x width: 235x155 mm, weight: 403 g, 69 Illustrations, color; 19 Illustrations, black and white; V, 251 p. 88 illus., 69 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Social Networks
  • Izdošanas datums: 02-Aug-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030412539
  • ISBN-13: 9783030412531
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.

Chapter1. Studying the Weaponization of Social Media: Case Studies of
Anti-NATO Disinformation Campaigns.
Chapter2. Cognitively-Inspired Inference
for Malware Task Indentation.
Chapter3. Beyond the Silk Road: Assessing
Illicit Drug Marketplaces on the Public Web.
Chapter4. Protecting the Web
from Misinformation.
Chapter5. Social Media for Mental Health: Data,
Methods, and Findings.
Chapter6. Twitter Bots and the Swedish Election.-
Chapter7. Automated Text Analysis for Intelligence Purposes: A Psychological
Operations Case Study.
Chapter8. You are Known by Your Friends: Leveraging
Network Metrics for Bot Detection in Twitter.
Chapter9. Inferring Systemic
Nets with Applications to Islamist Forums.