Title: Topic analysis of statistical journals: A vector space model approach
Authors: Charlene Mae Celoso - University of the Philippines Diliman (Philippines) [presenting]
Abstract: From its early stages up to today, the field of statistics has gone through several developments. With increased availability of computational tools, the problems that statisticians are able to tackle have changed through the years. Abstracts of articles in several prominent statistics journals are analyzed via a vector space model approach to uncover underlying concepts that have emerged in different time periods. From such models, visualizations can be created using semantic maps to discover topics that are grouped similarly.