A computational approach to studying how narratives can promote and support the reception of atypicality

Among the lessons learned from the recent pandemic is the importance of embracing the unconventional.

Indeed, atypical approaches have proved to be a key strategic resource for coping with unpredictable events, promoting socio-cultural transformation, and expanding the capacity to deliver valued goods and services.

However, although a departure from what is a standard positioning within socio-cultural domains may open up pathways to exceptional impact, existing research shows that atypical ideas, products, or actors generate mistrust and encourage rejection as they are subject to skepticism and face a higher risk of being considered ambiguous or illegitimate.

This project's aim is to study how narratives can support the reception of atypicality and stimulate its diffusion.

Narratives are powerful means of sustaining the alignment between actions and established conventions, especially in the face of situations that depart from expectations or definitions of what is considered contextually normal.

NARR-ATY-VES (Narratives for Atypicality) aims to 1) develop an understanding of the role of narratives' content and structure in promoting and supporting the evaluation of atypicality and 2) introduce an innovative computational approach based on cutting-edge Natural Language Processing (NLP) techniques to model two fundamental dimensions of narratives, namely their contextual embeddedness and their sequential unfolding based on cutting-edge Natural Language Processing (NLP) techniques, to map narrativity, i.e., the set of narrative elements that characterize the complex nature of narratives.

Through this hands-on 2-year research project, the Researcher's knowledge and skill will be enhanced enormously, and he shall be en route to becoming an expert in this field.