https://github.com/codeofrahul/nlp-twitter-sentiment-analysis-project
Analyze sentiment in text effortlessly, gaining insights into public opinion and customer feedback. Using NLP and machine learning, it understands nuanced emotions beyond keyword matching. The results are displayed in an intuitive Streamlit UI, making sentiment analysis accessible and actionable for all.
https://github.com/codeofrahul/nlp-twitter-sentiment-analysis-project
Last synced: 11 months ago
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Analyze sentiment in text effortlessly, gaining insights into public opinion and customer feedback. Using NLP and machine learning, it understands nuanced emotions beyond keyword matching. The results are displayed in an intuitive Streamlit UI, making sentiment analysis accessible and actionable for all.
- Host: GitHub
- URL: https://github.com/codeofrahul/nlp-twitter-sentiment-analysis-project
- Owner: CodeofRahul
- License: apache-2.0
- Created: 2025-02-21T02:51:17.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-02-21T10:58:32.000Z (11 months ago)
- Last Synced: 2025-02-21T11:42:45.386Z (11 months ago)
- Language: C
- Size: 36 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# NLP-Twitter-Sentiment-Analysis-Project
Analyze sentiment in text effortlessly, gaining insights into public opinion and customer feedback. Using NLP and machine learning, it understands nuanced emotions beyond keyword matching. The results are displayed in an intuitive Streamlit UI, making sentiment analysis accessible and actionable for all.
## ✨ Features
- **Data Collection**: Uses Twitter dataset for sentiment classification.
- **Data Preprocessing**: Cleans text, removes stopwords, and tokenizes tweets.
- **Feature Engineering**: TF-IDF vectorization and word embeddings.
- **Model Training**: Implements ML models to train the model.
- **Performance Evaluation**: Accuracy, F1-score, and Confusion Matrix.
## Setup
1. Clone this repository.
```python
git clone https://github.com/CodeofRahul/NLP-Twitter-Sentiment-Analysis-Project.git
cd NLP-Twitter-Sentiment-Analysis-Project
code .
```
2. Install Dependencies
```python
pip install -r requirements.txt
```
3. Run the Analysis
4. Run the Streamlit App
```python
streamlit run app.py
```
## Setup Instructions
- To create environment = `conda create -p python=3.8 -y`
- To check available envs = `conda env list`
- To check available envs = `conda info --envs`
- To activate environment = `conda activate `
- To install requirements.txt = `pip install -r requirements.txt`
- To check install packages = `pip list`
- To check detailed about package = `pip show package_name`
- To install package = `pip install package_name`
- To uninstall package = `pip uninstall package_name`
- To save all packages of env to a requirements.txt file = `pip freeze > requirements.txt`
## Git commands
- To add all file = `git add .`
- To add any particular file = `git add `
- To commit = `git commit -m "commit message"`
- To push the code = `git push origin main`
### **Problem**:
while working on this project i have faced a problem `VS Code Not Responding - freeses - When Opening Terminal. My VS Code version is 1.97
### **Solution 1**:
```
Download previous version of VSCode v.1.96
```
### **Solution 2**:
```
Go to Setting --> Terminal > Integrated: GPU Acceleration > Change from auto to off
```
**🤝 Contributing**
Contributions are welcome! Feel free to fork this repo, create a feature branch, and submit a PR.