Topic Modeling on Thomas Hobbes's Leviathan using BERTopic

This repository contains the code used to perform topic modeling on Thomas Hobbes's Leviathan using BERTopic. The purpose of this project is to identify the main topics discussed in the text and visualize them in a way that is easily understandable.

Getting Started

You can download a copy of Thomas Hobbes's Leviathan from the Project Gutenberg website: https://www.gutenberg.org/ebooks/3207. Once you have downloaded the text, you can upload it to Google Colab and run the code provided in the topic_modeling.ipynb notebook.

Dependencies

The following dependencies are required to run the code:

pandas

matplotlib

seaborn

scikit-learn

hdbscan

bertopic

These dependencies can be installed using pip.

Results

The main output of the project is a visualization of the topics identified in the text. The visualization shows the distribution of topics across the text and allows users to explore the most common terms associated with each topic.

Contributing

If you would like to contribute to the project, please fork the repository and submit a pull request with your changes. We welcome contributions of all kinds, including bug fixes, new features, and improvements to the documentation.