Mining Literary Trends: A Tool for Digital Library Analysis

Digital Libraries, especially large ones, need advanced tools for analyzing and interpreting their content. This paper introduces a novel Web-based tool designed to support library users in browsing and examining the content of digital libraries, and in extracting and interpreting high-level information from them. Leveraging external data and metadata repositories, our software uses state-of-the-art solutions in Natural Language Processing and Visualization to analyze and identify thematic trends and clusters over time. We describe the tool’s architecture and functionality, showing its effectiveness in tracking the evolution of topics along time within a textual corpus. We further illustrate it through a case study that analyzes two decades of scholarly articles from an established conference on Digital Libraries, showcasing the tool’s potential to help in understanding past and current academic research, and to guide future trajectories in this field.