Open Source Intelligence and Cyber Crime: Social Media Analytics

ISBN-13: 9783030412500 / Angielski / Twarda / 2020 / 251 str.

Mohammad A. Tayebi; Uwe Glasser; David B. Skillicorn

Spis treści

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.

Blurb

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.