Using Sentiment Analysis to investigate Sandro Abruzzese's literary works

The dataset was created to support a comparative geo-affective analysis of Sandro Abruzzese’s literary works, with a focus on Casa per casa and Niente da vedere. Starting from digitized and normalized texts (typographic cleaning, diacritic and punctuation harmonization, and segmentation), place names (toponyms) were extracted and their occurrences were counted by work and in the aggregated corpus (ALL). Each toponym was then enriched with geographic information (latitude/longitude coordinates, when available) and with a semantic–affective profile computed through SenticNet, including polarity and the Hourglass dimensions (attitude, introspection, sensitivity, temper). In parallel, toponyms were embedded in AffectiveSpace and summarized via Principal Component Analysis (PCA) to obtain a compact 2D representation (PC1–PC2) suitable for cross-text comparison. Finally, clustering was performed on the geo-affective feature set (k = 5), generating cluster labels and interpretable descriptors for each group. The resulting dataset is delivered in a tabular format (CSV), ready for statistical exploration, visualization, and GIS integration.