https://github.com/suraj-sedai/sentiment-analysis
This project classifies tweets from Twitter into positive, negative, or neutral categories using natural language processing (NLP) techniques.
https://github.com/suraj-sedai/sentiment-analysis
Last synced: 4 months ago
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This project classifies tweets from Twitter into positive, negative, or neutral categories using natural language processing (NLP) techniques.
- Host: GitHub
- URL: https://github.com/suraj-sedai/sentiment-analysis
- Owner: Suraj-Sedai
- Created: 2025-02-21T20:27:09.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-02-22T04:05:34.000Z (4 months ago)
- Last Synced: 2025-02-22T04:24:07.315Z (4 months ago)
- Language: Jupyter Notebook
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Sentiment Analysis Project
## 📌 Description
This project performs sentiment analysis on user comments using **TextBlob**. The data is cleaned using **NLTK** before applying sentiment classification.## 📂 Project Structure
```
Sentiment-Analysis/
├── data/
│ ├── raw_sentiment_data.csv # Store the dataset here
├── notebooks/
│ ├── sentiment_analysis.ipynb # Jupyter Notebook for analysis
├── scripts/
│ ├── preprocess.py # Text cleaning functions
│ ├── analyze.py # Sentiment analysis function
├── requirements.txt # List of dependencies
├── README.md # Project documentation
├── .gitignore # Ignore unnecessary files
```## 🛠Installation
1. Clone this repository:
```bash
git clone [https://github.com/Suraj-Sedai/Sentiment-Analysis.git]
```
2. Navigate to the project folder:
```bash
cd Sentiment-Analysis
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```## 🚀 How to Use
Run the Jupyter Notebook inside `notebooks/` to see the sentiment analysis in action.## 📊 Example Output
| Comment | Sentiment |
|---------|----------|
| I love this product! | Positive |
| This is the worst experience ever. | Negative |## 🎯 Features
- Data Cleaning with **NLTK**
- Sentiment Analysis using **TextBlob**
- Data Visualization with **Matplotlib & Seaborn**---