Svevo's Letters Corpus Analysis

Dive into the world of Italo Svevo's letters, uncovering the predominant themes and sentiments using Machine Learning and Data Mining techniques.

Project Contributors

• Valeria Insogna
• Roberta Pascale
• Cecilia Zagni

Objective

Analyze Italo Svevo's epistolary corpus to extract primary topics and sentiments using text mining methods, shedding light on the writer's thematic evolution over time.

Dataset

• Size: 894 letters from 1885 to 1928
• Nature: Multilingual corpus with Italian as the primary language
• Features: Letters content, recipients, language, date, sender & receiver location

Techniques

• Topic Modeling: Latent Dirichlet Allocation (LDA)
• Sentiment Analysis: NRC Word-Emotion Association Lexicon

Key Findings

• Dominant topics include "Literature", "Travels", "Leisure", and "Relationships".
• Letters reveal heightened positivity during Svevo's peak success years and negativity linked with personal losses.

Report

A curated list of references backing the methodology and approach can be found here.