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Open Source Intelligence and Cyber Crime : Social Media Analytics / edited by Mohammad A. Tayebi, Uwe Glässer, David B. Skillicorn.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in social networks 2190-5428
- Lecture Notes in Social Networks, 2190-5428
- Language:
- English
- Subjects (All):
- Computer security.
- Computational intelligence.
- Sociophysics.
- Econophysics.
- Computer crimes.
- Data mining.
- Machine learning.
- Systems and Data Security.
- Computational Intelligence.
- Data-driven Science, Modeling and Theory Building.
- Cybercrime.
- Data Mining and Knowledge Discovery.
- Machine Learning.
- Local Subjects:
- Systems and Data Security.
- Computational Intelligence.
- Data-driven Science, Modeling and Theory Building.
- Cybercrime.
- Data Mining and Knowledge Discovery.
- Machine Learning.
- Physical Description:
- 1 online resource (V, 251 pages) : 88 illustrations, 69 illustrations in color.
- Edition:
- First edition 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-41251-7
- 9783030412517
- Access Restriction:
- Restricted for use by site license.
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