Starting from the concept of Made in Italy, the study aims to investigate the interconnection of the variables and the values linked to Italian culture and the fashion industry. The approach of this work is based on text mining techniques, in particular, considering Latent Dirichlet Allocation (LDA) as a specific topic modeling approach. The comprehensive methods include exploring the text to find and identify the most relevant recurring concepts and terms. These techniques are considered on an innovative textual dataset as abstracts of the scientific literature of the relevant fields explored (Gender, Fashion, and Italy). In this way, we have considered the literature on the field trying to identify the existing relationships between culture, gender, and relevant innovations in the fashion sector. The originality in the methodology applied to scientific abstracts is their ability to aggregate relevant scientific results. In this way, LDA, as a topic modeling approach, can discover and identify the latent structure of the documents considered (the corpus of the scientific literature). In this sense, we summarize and identify the most relevant themes in the text and this way of the literature. The research has shown relevant results that reveal the association between cultural values and the development of the fashion industry, where women play a fundamental role in innovation. Female entrepreneurs in the fashion sector are a driver of innovation, creating new markets and revenue growth.