The use and linguistic analysis of military and political euphemisms in web communication play a crucial role in understanding the complexities of discourse surrounding armed conflicts and political events. This study shows that using computer-based content analysis to study web content about the Russian-Ukrainian war offers researchers a powerful and efficient means of uncovering patterns, sentiments, and narratives in the digital sphere. Thisodology uses natural language processing and machine learning techniques to identify and classify the sentiment or emotion expressed in the text, whether positive, negative, or neutral. The findings emphasize the importance of understanding the socio-political context in which these expressions emerge. The study reveals the strategies behind eu-me language and its impact on public discourse, providing a foundation for future research to explore the ethical implications of language manipulation and the role of digital communication in shaping contemporary conflicts.