Computational interpretations of 'Invisible Cities' and its public reflections by KU Leuven
In the realm of digital humanities, the essence of literary works often remains veiled in abstract prose and metaphors, awaiting intricate analysis. This project unveils the depths of Italo Calvino's "Invisible Cities" by harnessing the power of text analytics and visualization.
The primary objective was to shed light on the underlying themes and sentiments of both the book and its reader reviews. By employing the BERTopic model, a state-of-the-art text analytics technique, we extracted latent topics that provide a fresh perspective on Calvino's masterpiece. This approach not only enabled the identification of core themes but also revealed intriguing patterns in reader reviews, capturing their sentiments and associations with other literary works.
The visualization aspect is the heart of this project, making use of techniques like edge bundling and the Sankey Diagram to present intricate data in an engaging, interactive, and user-friendly manner. In addition to the visualization offering profound insights into the book's and review's topics, it also highlights patterns in reader behaviors, such as commenting trends during the COVID-19 lockdown.
Targeted at both scholars and avid readers of Calvino's work, this visualization serves as a bridge between computational methods and literary analysis. It's not just a depiction of data; it's a narrative, a story of stories, presented in a way that combines the rigor of research with the beauty of visual art.