(untitled) (Innovations in Science and Technologies, 2025)
The influence of media discourse has been and is currently still affecting communication patterns of all sizes and in many cultural contexts, and cross-linguistic research still lacks profound insights into the comparative implications of this phenomenon. The purpose of this article is to use statistical analysis related technology to analyze the characteristics of English and Uzbek data for the different types of linguistic data and different levels of interpretive needs of participants in the entire media analysis process. This study addresses this gap by drawing on a rich body of empirical data collected from media texts and audience responses in a comparative case study of English and Uzbek media discourse. Linguistic features of all utterances in the datasets get aggregated in a number of ways into a single analytical framework for researchers whose accuracy is critical for valid interpretations. The study designs the data correlation relationship of the regression model elements, define the relationship between the discourse types, and implement the regression-based method. At the same time, according to the classification of cross-linguistic features, mapping of semantic relationships, filtering redundant information, and graphical visualization are conducted. By providing a comprehensive understanding of how media discourse affects cross-cultural communication, the insights from our analysis contribute to linguistic scholarship, media studies, and applied communication research alike. The paper concludes by identifying several promising areas for future cross-linguistic investigation.