Explaining the distribution of implicit means of misrepresentation: A case study on Italian immigration discourse

This study analyzes Fillmore's frames in a large corpus of Italian news headlines concerning migrations, dating from 2013 to 2021 and taken from newspapers of diverse ideological stances. Our goal is to assess whether, how, and why migrants' representation varies over time and across ideological stances. Our approach combines corpus-assisted critical discourse analysis with cognitive linguistics. We present a new methodology that exploits SocioFillmore, a tool integrating a novel Natural Language Processing model for automatic frame annotation into a web-based user interface for exploring frame-annotated corpora. In our corpus, the frequency distribution of frames varies over time according to detectable contextual factors. Across political stances, instead, the most frequent frames remain more constant: both right-winged and left-winged news providers contribute to reifying migrants into non-agentive entities. Further, in religious (Christian) press migrants are given a more humanizing depiction, but they still often appear in non-agentive roles. The distributions of frames can be explained by the fact that the latter act as indirect, routinized, and implicit means of (mis)representation. We suggest that framing entails inferential operations that take place unconsciously and can therefore escape the cognitive screening not only of those who receive discourse, but also of those who (re)produce it.