Unveiling Extremism: Leveraging Digital Data Mining Strategies - Alhadrawi, Ali Khudayer Abdulabbas; Ezzerouali , Souad; Jawad , Ameer Rajeh; AL-BARASHDI, Saleh; Al-Hadrawi, Baqer Khudair; Al-hadrawi, Kais Khudhair (Journal of Ecohumanism, 2024)
In the theoretical exploration of "Unveiling Extremism: Leveraging Digital Data Mining Strategies," the intricate web of extremist behavior is dissected through the lens of digital data mining. By utilizing advanced computational techniques, this study delves into the depths of online platforms, analyzing patterns, sentiments, and interactions to uncover the underlying mechanisms of extremism. The focus lies not only on identifying extremist content but also on understanding the processes that lead individuals towards radicalization. Through theoretical modeling and simulation, this research seeks to map out the pathways of radicalization, shedding light on the factors that contribute to the formation and spread of extremist ideologies. Moreover, the study examines the efficacy of various digital data mining strategies in detecting and countering extremism, proposing innovative approaches to enhance the effectiveness of online monitoring and intervention. Ultimately, this theoretical exploration serves as a foundation for developing proactive measures to combat extremism in the digital age, offering insights that can inform policy-making, intervention programs, and the design of online platforms.