🤖 AI Summary
This study addresses the lack of large-scale, standardized, and openly accessible datasets in metaphor research. To this end, we constructed a high-quality Italian metaphor corpus comprising 997 metaphors drawn from both everyday and literary contexts, each manually annotated with multidimensional cognitive and linguistic metrics—including familiarity, word frequency, imageability, and concreteness. We introduce “inclusivity” as a novel metric to support non-discriminatory linguistic analysis and developed an interactive web platform enabling multi-criteria querying and visual exploration. Annotation reliability and validity were confirmed through correlation-based statistical validation. Currently the largest open-source Italian metaphor corpus, this resource significantly enhances cross-experimental reusability and advances standardization, reproducibility, and open science practices in metaphor research.
📝 Abstract
Research on metaphor has steadily increased over the last decades, as this phenomenon opens a window into a range of processes in language and cognition, from pragmatic inference to abstraction and embodied simulation. At the same time, the demand for rigorously constructed and extensively normed experimental materials increased as well. Here, we present the Figurative Archive, an open database of 997 metaphors in Italian enriched with rating and corpus-based measures (from familiarity to lexical frequency), derived by collecting stimuli used across 11 studies. It includes both everyday and literary metaphors, varying in structure and semantic domains. Dataset validation comprised correlations between familiarity and other measures. The Figurative Archive has several aspects of novelty: it is increased in size compared to previous resources; it includes a novel measure of inclusiveness, to comply with current recommendations for non-discriminatory language use; it is displayed in a web-based interface, with features for a flexible and customized consultation. We provide guidelines for using the Archive in future metaphor studies, in the spirit of open science.