AI-based OSINT (Open Source Intelligence): Social Media Monitoring, Collections, Investigations/Reporting, Analytics Training by Tonex
This comprehensive training course, AI-based OSINT (Open Source Intelligence): Social Media Monitoring, Collections, Investigations/Reporting, Analytics, offered by Tonex, is designed to equip professionals with advanced skills in leveraging artificial intelligence for Open Source Intelligence (OSINT) purposes. Participants will gain hands-on experience in utilizing cutting-edge tools and techniques to monitor social media, collect data, conduct investigations, generate insightful reports, and perform analytics for enhanced decision-making.
Learning Objectives:
- Understand the fundamentals of social media intelligence (SMI) analysis.
- Learn advanced techniques for collecting, analyzing, and interpreting social media data.
- Gain proficiency in using AI and machine learning algorithms for SMI analysis.
- Develop skills in identifying trends, patterns, and insights from social media content.
- Explore strategies for conducting investigations and reporting based on SMI findings.
- Enhance knowledge of ethical and legal considerations in SMI analysis.
Target Audience:
- Law enforcement professionals
- Intelligence analysts
- Cybersecurity professionals
- Marketing and advertising professionals
- Researchers and academics
- Government agencies
- Private sector organizations
Course Modules:
Module 1: Introduction to Social Media Intelligence (SMI)
- Overview of SMI concepts and applications
- Importance of SMI in various domains (security, marketing, research)
- Ethical and legal considerations in SMI analysis
Module 2: Advanced Social Media Data Collection Techniques
- Automated data scraping and crawling methods
- API-based data retrieval from social media platforms
- Geo-location and geo-fencing for targeted data collection
- Strategies for handling big data in SMI analysis
Module 3: Natural Language Processing (NLP) for SMI Analysis
- Introduction to NLP techniques for text analysis
- Sentiment analysis of social media content
- Named entity recognition and topic modeling
- Extracting actionable insights from text data
Module 4: Image and Video Analysis in SMI
- AI-based image recognition and classification
- Detecting objects, faces, and logos in multimedia content
- Analyzing visual content for sentiment and context
- Deep learning models for video analysis and anomaly detection
Module 5: Network Analysis and Influence Measurement
- Social network analysis (SNA) for identifying connections and communities
- Measuring influence and impact on social media platforms
- Identifying bots, trolls, and fake accounts using network analysis
- Tracking information diffusion and virality of content
Module 6: Investigative Techniques and Case Studies
- Conducting SMI-based investigations
- Techniques for corroborating and verifying social media data
- Case studies illustrating successful SMI investigations
- Legal and ethical considerations in using SMI as evidence
Module 7: Reporting and Visualization
- Creating informative and visually appealing reports from SMI findings
- Data visualization techniques for presenting insights
- Tools for storytelling and narrative building
- Tailoring reports for different stakeholders and audiences
Module 8: Future Trends and Emerging Technologies in SMI
- Exploring advancements in AI and machine learning for SMI
- Predictive analytics and forecasting in social media trends
- Challenges and opportunities in the evolving landscape of SMI
- Strategies for staying updated and adapting to new technologies