This paper presents an annotation scheme developed to analyze linguisticaccessibility and inclusivity in Italian cancer-related informational materials.The scheme combines metadata annotation, qualitative analysis of textual andvisual features, and automatically extracted measures of linguistic complexitycapturing structural, lexical, and probabilistic properties of the texts. Abrief case study demonstrates how the proposed framework can be applied tocompare documents and identify different sources of linguistic difficulty. Theapproach provides a replicable methodological basis for large-scale analyses ofhealth communication materials.

Over the past two decades, the rise of new technologies and social networks has significantly shaped written language, imbuing it with characteristics akin to the spoken language. This study reports on the ongoing initiative to build the WhAP corpus, a resource featuring WhatsApp conversations in Italian, encompassing both written and spoken messages and totaling at present more than 400.000 tokens, 89 conversations, and 194 participants from diverse age groups and geographical regions of Italy. More specifically, this paper focuses on the practical steps involved in the construction of the resource. Once publicly accessible, the WhAP Corpus will enable in-depth linguistic research on the language used on WhatsApp, which shows unique features such as the blending of written and spoken elements.