Topic Modeling Techniques for 2026: Seeded Modeling, LLM Integration, and Data Summaries

The content introduces advanced topic modeling techniques, focusing on seeded topic modeling, integration with Large Language Models (LLMs), and training on summarized data. It explains how the KeyNMF model uses a 'seed phrase' to guide the discovery process towards topics relevant to a user's specific interest. The article also proposes using LLM-generated summaries to improve model accuracy and leveraging generative models to automatically label topics and provide descriptions. These methods are illustrated using a corpus of European Central Bank communications to extract stable and economically meaningful topics.