Download Steam reviews for any game. Available on PyPI.
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Updated
Aug 25, 2025 - Python
Download Steam reviews for any game. Available on PyPI.
Easily create, format and preview your Steam reviews in real-time
Statistics of Steam reviews.
[PoC] An experimental editor that converts Markdown to Steam review/wiki formatting
Study the relationship between review numbers and sales for Steam games
Count reviews for Steam and non-Steam purchases. Featured in Ars Technica.
Sample Steam reviews with the GPT-2 language model.
Sample Steam reviews with different approaches.
Data available to compute statistics of Steam reviews.
Steam review creator made with Astro 4. Available in Spanish too!
This project uses Natural Language Processing (NLP) and Machine Learning techniques to analyze user reviews of top-selling games on the Steam platform. The goal is to detect bug-related reviews using keyword filtering, assess user sentiment (positive, neutral, negative), and group similar games using clustering methods.
This project uses Natural Language Processing (NLP) and Machine Learning techniques to analyze user reviews of top-selling games on the Steam platform. The goal is to detect bug-related reviews using keyword filtering, assess user sentiment (positive, neutral, negative), and group similar games using clustering methods.
Data available to compute regional rankings of hidden gems.
Sentiment Analysis and Topic Modeling on the Steam Game Reviews using Hadoop and Mahout
A scraper written in Rust to gather Steam user reviews along with models in Python.
Automatically curate a list of games using the same blurb [no longer maintained]
Steam review parsing CLI application that processes reviews in CSV format in a concurrent and multithreaded manner using the fork join model [1Q2025]
This repository contains a sentiment analysis project on Baldur's Gate 3 Steam reviews using natural language processing (NLP) techniques. It leverages machine learning and deep learning models to classify reviews as positive or negative. The project includes preprocessing steps, feature extraction, and performance evaluation across various models.
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