Background and Objective: The expansion of artificial intelligence, data-driven platforms, and recommender algorithms has transformed the information environment and individuals’ engagement with political reality, shifting cognitive warfare toward intelligent, personalized, and algorithm-driven processes. This study aimed to explain the mechanisms of the algorithmic reconfiguration of political perception in Iranian society within the context of intelligent cognitive warfare from 2021 to 2026.
Methods: This applied qualitative study employed Braun and Clarke’s thematic analysis. From a corpus of scholarly documents, strategic reports, and relevant analytical materials, 40 documents were selected through criterion-based purposive sampling and analyzed using MAXQDA. The coding process yielded 92 initial codes, 76 final codes, 27 basic themes, nine organizing themes, and three overarching themes.
Findings: Three overarching mechanisms were identified: “algorithmic engineering of encounters with political reality,” “cognitive–emotional activation,” and “reconstruction of the perception of political reality.” The final model revealed an eight-stage process extending from the datafication of political behavior and algorithmic selection to attention engineering, activation of cognitive biases, emotional arousal, reframing of political reality, narrative consolidation, and the reconfiguration of political perception.
Conclusions: The reconfiguration of political perception results from an interconnected chain of data-driven, algorithmic, cognitive, and emotional processes. The concept of the “algorithmic architecture of political perception” demonstrates that algorithms have moved beyond their role as mere intermediaries of message transmission and, by organizing visibility, attention, and interpretation, have become an influential technology of intelligent cognitive warfare.