https://github.com/armandfs/app-review-sentiment-analysis
This is a machine learning sentiment analysis project that is focused on creating sentiments on application reviews from Google Play Store. This project will scrape user review data from the application CrunchyRoll.
https://github.com/armandfs/app-review-sentiment-analysis
machine-learning python sentiment-analysis sklearn
Last synced: 27 days ago
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This is a machine learning sentiment analysis project that is focused on creating sentiments on application reviews from Google Play Store. This project will scrape user review data from the application CrunchyRoll.
- Host: GitHub
- URL: https://github.com/armandfs/app-review-sentiment-analysis
- Owner: ArmandFS
- Created: 2024-10-27T14:25:53.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-15T06:12:24.000Z (over 1 year ago)
- Last Synced: 2025-01-18T12:52:25.323Z (over 1 year ago)
- Topics: machine-learning, python, sentiment-analysis, sklearn
- Language: Jupyter Notebook
- Homepage:
- Size: 6.71 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# 📱💬 Crunchyroll Review Sentiment Analysis 📱💬
## ⭐ Project Overview ⭐
This project analyzes the sentiments of reviews for the **Crunchyroll app** on the Google Play Store 📊. Using **Natural Language Processing (NLP)** and **Machine Learning**, we aim to classify reviews as **positive**, **neutral**, or **negative**.
### ✨ Objectives ✨
- **Understand user sentiment**: Learn how to create a sentiment analysis model and implement it in a local Streamlit app.
- **Drive business decisions**: Listen to user feedback, understand criticism, and improve the app's performance and features.
### 🚀 Tech Stack 🚀
- **Python** : for computation and modeling.
- **Streamlit** : for an interactive web application.
- **Scikit-Learn** : for logistic regression, random forest, and TF-IDF vectorization.
- **NLTK** 🧠 for text preprocessing and analysis.
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### 📌 Key Features 📌:
- **Sentiment Classification**: Automatically classifies reviews as **positive**, **neutral**, or **negative**.
- **Real-Time Analysis**: Enter any review text and get sentiment analysis instantly.
- **Data Visualization**: Visualize sentiment distribution of Crunchyroll reviews.
Feel free to explore and contribute! 😊