Topic modeling is a technique that allows us to automatically analyze documents, detecting word and phrase patterns within them. It is used for the discovery of structures in a text body, automatically gathering word groups and similar expressions that can best characterize a set of documents.
Topic modeling employs unsupervised and supervised statistical machine learning techniques to identify patterns in a large number of texts. It can, therefore, facilitate the understanding, organizing, and summarizing of huge text datasets as a way to obtain recurring patterns of words in textual material.
This data science tool can be very effective in companies, as for example, by applying topic modeling analysis, companies are able to deploy simple and repetitive tasks to machines, leaving employees with more time for other important activities.