2024/08/15 by Giovanni Spitale, Federico Germani, Nikola Biller‐Andorno · 1 voice
Biochemistry, Genetics and Molecular Biology · Decision Sciences · Social Sciences · #Academic Publishing and Open Access #Biomedical Text Mining and Ontologies #Computational and Text Analysis Methods
paper · pdf · doi:10.1016/j.heliyon.2024.e36351
openalex publication_date 2024/08/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Background: The ever-increasing volume of academic literature necessitates efficient and sophisticated tools for researchers to analyze, interpret, and uncover trends. Traditional search methods, while valuable, often fail to capture the nuance and interconnectedness of vast research domains. Results: TopicTracker, a novel software tool, addresses this gap by providing a comprehensive solution from querying PubMed databases to creating intricate semantic network maps. Through its functionalities, users can systematically search for desired literature, analyze trends, and visually represent co-occurrences in a given field. Our case studies, including support for the WHO on ethical considerations in infodemic management and mapping the evolution of ethics pre- and post-pandemic, underscore the tool's applicability and precision. Conclusions: TopicTracker represents a significant advancement in academic research tools for text mining. While it has its limitations, primarily tied to its alignment with PubMed, its benefits far outweigh the constraints. As the landscape of research continues to expand, tools like TopicTracker may be instrumental in guiding scholars in their pursuit of knowledge, ensuring they navigate the large amount of literature with clarity and precision.