The Stroke Research Panorama: A Natural Language Processing Based Topic Modeling Study

Introduction: The massive growth in scholarly publications presents a hurdle for researchers, given the considerable amount of time required to compile and interpret these findings. Natural language processing and topic modeling can accelerate the condensation of academic literature. It offers an innovative method for discovering hidden themes within vast and diverse literature data, providing researchers with insights into research fields. This study aims to demonstrate the potential of these tools; we focused on stroke research, a significant global health issue.

Methods: Articles for our study were obtained from the journals Stroke, International Journal of Stroke, European Stroke Journal, Translational Stroke Research, and Journal of Stroke and Cerebrovascular Diseases. On May 11, 2023, articles were retrieved from the Scopus database. Included were only "Article" and "Review" document types. We employed BERTopic, a topic modeling technique that uses Bidirectional Encoder Representations from Transformers. Following training, the model generated a collection of topics and representative documents. Following an analysis of keywords and representative documents, the authors labeled these topics by consensus. A trend analysis for the current decade was conducted.

Results: First, 35779 documents were collected. When the inclusion criteria were applied, 26732 documents were included and classified into 30 distinct categories. “Animal Models”, “Rehabilitation”, “Reperfusion Therapy”, “Small Vessel Disease”, “Cerebral Blood Flow”, “Intracranial Aneurysms”, “Cervical Artery Dissection”, “Intracerebral Hemorrhage”, “Biomarkers”, and “Cerebral Venous Thrombosis” were the ten most prevalent topics. The linear regression models provided an overview of the current decade's trends. They identified "Emboli," "Medullary and Cerebellar Infarcts," and "Glucose Metabolism" as the three most popular topics.

Conclusion : Our BERTopic-driven study provides a revealing look at stroke research, illuminating prevalent trends and evolving research interests. From "Animal Models" to "Environmental Factors," our study revealed a vast array of research fields. Furthermore, our trend analysis spotlighted emerging hot topics like "Emboli," "Medullary and Cerebellar Infarcts" and "Glucose Metabolism".