METAPHORICAL FRAMINGS IN THE NEW YORK TIMES ONLINE PRESS REPORTS ABOUT CHATGPT

Through a combined quantitative-qualitative approach the paper aims to explore the densities and possible rhetorical effects of the most common metaphorical framings used in the New York Times online press reports about ChatGPT. The theoretical framework is based on the main tenets of conceptual metaphor theory (Lakoff and Johnson 2003[1980]), frame semantics (Fillmore 1982), and image schema theory (Johnson 1987). The initial stage involved the construction of a small specialized corpus which was tagged manually for the analysis in WordSmith Tools 6.0. Metaphor identification was conducted in line with MIPVU (STEEN et al. 2010). Quantitative analysis showed the highest density for containment, motion, and force metaphors. Living being, tool, conflict, and machine metaphors were also present, but not as frequent. The linear regression model (motion, force, living being) explained 61% of variance in the density of containment metaphors, and it was significant (p=.002). Additional linear regression models have also been tested. The results suggest the potential for interaction of these metaphor groups when they cooccur in discourse (i.e., they may work in concert to construct a specific viewpoint). Qualitative analysis showed a range of possible rhetorical effects that the identified metaphorical framings may play (e.g., making AI more appealing by framing it as a living being or tool, raising doubts about the use of AI by constructing borders and containers, or framing AI as a threat). Results of qualitative analysis should be understood as testable hypotheses that remain to be further explored and validated in experimental settings.