GPTopic: Dynamic and Interactive Topic Representations

TL;DR

GPTopic is a software tool that uses large language models to generate dynamic, interactive, and more accessible topic representations, enhancing exploration and understanding of large text corpora.

Contribution

It introduces an interactive chat-based interface leveraging LLMs for more comprehensive and user-friendly topic modeling.

Findings

Enables dynamic exploration of topics through chat interface

Improves accessibility of topic modeling for non-experts

Provides a more nuanced understanding of topics beyond top words

Abstract

Topic modeling seems to be almost synonymous with generating lists of top words to represent topics within large text corpora. However, deducing a topic from such list of individual terms can require substantial expertise and experience, making topic modelling less accessible to people unfamiliar with the particularities and pitfalls of top-word interpretation. A topic representation limited to top-words might further fall short of offering a comprehensive and easily accessible characterization of the various aspects, facets and nuances a topic might have. To address these challenges, we introduce GPTopic, a software package that leverages Large Language Models (LLMs) to create dynamic, interactive topic representations. GPTopic provides an intuitive chat interface for users to explore, analyze, and refine topics interactively, making topic modeling more accessible and comprehensive. The corresponding code is available here: https://github.com/ArikReuter/TopicGPT.