Artificial intelligence and network science as tools to illustrate academic research evolution in interdisciplinary fields: The case of Italian design

Abstract

In this paper, we explore the application of Artificial Intelligence and network science methodologies in characterizing interdisciplinary disciplines, with a specific focus on the field of Italian design, taken as a paradigmatic example. Exploratory data analysis and the study of academic collaboration networks highlight how the field is evolving towards increased collaboration. Text analysis and semantic topic modelling identified the evolution of research interest over time, defining a ranking of pairs of keywords and three prominent research topics: User-Centric Experience Design, Innovative Product Design and Sustainable Service Design. Our results revealed a significant transformation in the field, with a shift from individual to collaborative research, as evidenced by the increasing complexity and collaboration within groups. We acknowledge the limitations faced by this work, suggesting that the methodology may be primarily suitable for bibliometric and more silos-like disciplines. However, we emphasize the urgency for the scientific community to address the future of research not indexed by large open-access databases like OpenAlex.