Topic Modeling of Research Fields: An

This paper addresses the problem of scientific research analysis. We use the topic model Latent Dirichlet Allocation [2] and a novel classifier to classify re-search papers based on topic and language. Moreover, we show various insightful statistics and correlations within and across three research fields: Linguistics, Computational Linguistics, and Education. In particu-lar, we show how topics change over time within each field, what relations and influences exist between top-ics within and across fields, as well as what trends can be established for some of the world’s natural lan-guages. Finally, we talk about trend prediction and topic suggestion as future extensions of this research