Nowadays, a significant portion of our time is spent on the Internet. We read Web pages, tutorials, news, and social media posts throughout our day. This has resulted in a surge in the amount of text that is accessible online, consequently leading to an increase in text analysis tools, techniques, and, specifically, Natural Language Processing (NLP) tools.
Thanks to the utilization of Artificial Intelligence techniques and algorithms, text analysis is now simpler and more comprehensive. It enables us to automatically translate texts, produce summaries, identify emotions from texts, and even generate written content entirely on its own.
Unfortunately, there has been an increase in terrorist attacks within Europe in recent
years. With recent attacks in multiple cities throughout Europe, authorities are compelled to investigate these organizations thoroughly in order to comprehend their methods of operation and recruitment and ultimately put an end to them. Analyzing their magazines, such as Dabiq and Rumiyah, which serve as recruitment and propaganda tools, can be invaluable in understanding their beliefs and practices.
In this project, texts were collected from the two primary Islamic State magazines, Dabiq and Rumiyah. Utilising data analysis techniques, the texts were processed and analysed with various classifiers from Senpy API plugins for a thorough analysis of each text. Since the sheer amount of data generated prohibits a subjective analysis, we have processed the responses and created Tableau Dashboards to present the analysis in a more comprehensible way visually and to facilitate the analysis.