Centro de Documentação da PJ
Analítico de Periódico
CD 358
Development of an intelligence gathering framework for analysing cyber extremism on social media networks [Recurso eletrónico] / Ala Berzinji, Rawaz A Alrahman F Muhammed, Danial Abdulkareem Muhammed
International Journal of Cyber Criminology, Vol. 18, n. 1 (January-June 2024), p. 195-209
Ficheiro de 456 KB em formato PDF.
CIBERTERRORISMO, REDE SOCIAL, INFORMÁTICA FORENSE, LINGUAGEM DE PROGRAMAÇÃO, PREVENÇÃO CRIMINAL, INTELIGÊNCIA ARTIFICIAL
This proposal outlines a systematic approach to collecting and analysing data from social media platforms to understand and combat cyber radicalism. The plan employs Python, Selenium, and MongoDB to gather, store, and process large, unstructured datasets. Advanced natural language processing (NLP) techniques and machine learning models are integrated to analyse communication patterns and sentiment on these platforms. Studies have highlighted that extremist rhetoric on social media is often characterised by heightened negative sentiment and explicit language associated with violence. A temporal analysis of activity spikes revealed correlations between radicalisation efforts and significant real-world events. Additionally, network mapping identified key actors and coordinated groups involved in the dissemination of extremist content. These findings contribute to the development of effective tools for monitoring and addressing online radicalisation, offering practical insights for law enforcement and intelligence agencies. The study recommends expanding data collection efforts, incorporating multilingual capabilities, and deploying sophisticated algorithms for early detection. Furthermore, it emphasizes the importance of ethical frameworks to balance security measures with privacy considerations. Such advancements would represent a significant step towards mitigating extremist threats and enhancing global security in the digital era.
