The research group focuses on applying Natural Language Processing models, particularly in the areas of Topic Mining and Sentiment Analysis, to texts of very diverse nature and chronology, with the aim of verifying results not only through close reading, but also in a comparative, interlinguistic, and intercultural perspective.

Two main research directions have been pursued:

• Theatre and Cconomy in Ancient Greece: The aim of the project is an in-depth investigation of the economic and political lexicon in 5th- and 4th-century BCE theatre and, in a second phase, in contemporary oratory texts. Using Digital Humanities tools (in particular, distributional semantics and topic mining), a semantic and thematic analysis of the identified occurrences will be conducted, not only to define a new interpretative framework, but also to contribute to a cultural history of antiquity along two of its most relevant and fascinating dimensions.
• Sentiment Analysis and Gender Studies: The project also aims to investigate, from a comparative perspective, the results of applying Sentiment Analysis models to the emotional lexicon of women, both in textual corpora where they are the protagonists (starting with the Bible in various translations) and in literature and documents authored by women in the 16th–18th centuries (“women and knowledge”).

Technological Tools and Methods

• Natural Language Processing (NLP) models for the analysis of texts of diverse nature and chronology
• Topic Mining for the extraction and analysis of recurring themes in texts
• Sentiment Analysis for the investigation of emotional lexicon and affective content.
• Comparative, interlinguistic, and intercultural analysis techniques for textual data.
• Tools for distributional semantics and thematic analysis