Core Concepts
Large Language Models (LLMs) can enhance topic modeling by providing dynamic and interactive representations, making it more accessible and comprehensive.
Abstract
GPTopic introduces a software package that leverages Large Language Models (LLMs) to create dynamic and interactive topic representations. Traditional topic modeling often relies on static lists of top-words, which may not fully capture the complexity of topics. GPTopic aims to address this limitation by offering an intuitive chat interface for users to explore, analyze, and refine topics interactively. By utilizing LLMs, GPTopic allows for a more nuanced and comprehensive understanding of topics, making topic modeling more accessible to non-technical users. The software package enables users to generate concise names and descriptions for topics, engage with topics dynamically through a chat-based interface, and modify topics based on previous analyses.
Stats
500 top-words are used by default to extract a topic's title and description.
Over 10,000 documents are recommended for optimal topic identification.