Language in all its forms serves as the primary instrument through which media institutions ideologically interpellate audiences into their preferred discursive frameworks. During global crises such as warfare or the COVID-19 pandemic, audiences become particularly susceptible to media capture. Such crises enable media outlets to simultaneously report events and establish ideological hegemony within the audience's consciousness. This study examined this phenomenon across three Persian-language media outlets of IRIB, Iran International, and BBC Persian during the first five months of the COVID-19 pandemic. The principal methodological distinction of this research lies in its computational approach. All textual corpora were processed through a custom-built R programming language application, with statistical analyses executed within the same framework. Crucially, human agents were excluded from the initial corpus reading phase. The output subsequently underwent analysis via Fairclough's Three-Dimensional Model. This research thus pursued the objectives: a) Proposing an automated methodology for Critical Discourse Analysis (CDA) that eliminates human reading of source texts, b) Conducting a CDA examination of COVID-19 discourse across the aforementioned media outlets. Results indicated that the computational approach yields substantively accurate analyses, particularly for large-scale corpora. Retrospective application of Fairclough's model further revealed that long-term audience trust correlates strongly with two factors: consistency in central signifiers and eschewal of discursive polarization. Analysis demonstrates that IRIB and Iran International exhibited significantly greater inconsistency and radical positioning than BBC Persian.