The cognitive architecture of AI discourse: analyzing public perceptions through the event structure metaphor framework

Abstract

The rapid mainstream adoption of generative artificial intelligence (AI) has triggered intense and deeply polarized global discourse, frequently divided between systemic optimism (“hype”) and existential anxiety (“doom”). While contemporary literature predominantly arranges public perceptions of AI along static anthropomorphic gradients, empirical examinations analyzing digital discourse through the processual, dynamic lens of Cognitive Linguistics remain critically scarce. To address this gap, this study adopts a mixed-methods design integrating quantitative Corpus Linguistics with the interpretative depth of Critical Metaphor Analysis (CMA). By systematically identifying Peña Cervel’s (2003, 2012) foundational image-schematic configurations serving as primary master domains, this research investigates how these conceptual building blocks integrate into the macro-framework of Lakoff’s Event Structure Metaphor (ESM). It further extends this cognitive mapping into Musolff’s (2016) discourse scenarios to demonstrate how underlying embodied and socio-cognitive structures culminate in culturally conditioned digital discourse. Utilizing a compiled corpus of 5,000 Turkish YouTube comments (2019–2025) as a critical case study, our primary objective is to unveil the deep cognitive infrastructure through which everyday social actors conceptualize AI’s developmental trajectory. The findings reveal that rather than perceiving AI merely as a static agent, public discourse relies heavily on force-dynamic configurations—framing AI as an unfolding event structured by metaphorical paths, motion dynamics, and systemic barriers. By bridging corpus-driven frequencies with critical discourse dimensions, this study demonstrates how metaphorical frameworks actively license contrasting ideological positions and structure collective perceptions of AI as a socio-technological force.