Topic modeling is a type of statistical modeling used in natural language processing (NLP) to discover abstract topics that occur in a collection of documents. The primary goal is to identify the hidden thematic structure within a large set of text. Topic models help in organizing, understanding, and summarizing large datasets of textual information by grouping together words that frequently appear together.
New to topics? Read the docs here!