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A Sentiment Analysis Anomaly Detection System for Cyber Intelligence.

Roberta Maisano1, Gian Luca Foresti2

  • 1Computer Science Centre, University of Messina, Piazza Antonello, 2, 98122 Messina, Italy.

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Summary
This summary is machine-generated.

A new Sentiment Analysis system with Anomaly Detection (SAAD) predicts geopolitical shifts by analyzing social media. This cyber intelligence tool identifies manipulation and misinformation trends, proving effective in real-world scenarios.

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Cyber intelligenceOSINTanomaly detectionmachine learningsentiment analysis

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Area of Science:

  • Cyber Intelligence
  • Geopolitics
  • Computational Social Science

Background:

  • The 2030 UN goals emphasize global connectivity, making cyber intelligence crucial for geopolitical dynamics.
  • Cyberspace is a new battlefield where social media manipulation, misinformation, and deception are key weapons.
  • Understanding public sentiment on social media is vital for detecting emerging threats.

Purpose of the Study:

  • To propose a Sentiment Analysis system with Anomaly Detection (SAAD) capability.
  • To investigate social media sentiment using an OSINT-Deep Learning approach to predict suspicious anomaly trends on Twitter.
  • To develop a novel semi-supervised process for anomaly detection in critical areas.

Main Methods:

  • Developed a scalable and modular Sentiment Analysis system with Anomaly Detection (SAAD).
  • Utilized an Open-Source Intelligence (OSINT) and Deep Learning approach for social media sentiment analysis.
  • Implemented a new semi-supervised anomaly detection process and a time-dependent confusion matrix for model evaluation.

Main Results:

  • The SAAD system demonstrated suitability across different domains and areas.
  • The anomaly detection procedure effectively identified suspicious sentiment trends in social media data.
  • Experiments in the Sahel Region confirmed a link between detected negative sentiment anomalies and real-world geopolitical situations.

Conclusions:

  • The proposed SAAD system is a valuable tool for cyber intelligence and geopolitical analysis.
  • The novel anomaly detection method enhances the ability to identify potentially dangerous situations.
  • The system's effectiveness was validated through real-world experiments in the Sahel Region.