Here we introduce a novel bibliometric methodology based on natural language data processing for identifying emerging topics in science. Along with the usual practice of data collection and preprocessing, it includes a natural language processing technique and an innovative mathematical function data approximation, which better addresses the data fluctuations problem, allows to make predictions, as well as to introduce a specific measure of emergence.