Sentiment Analysis Project

Welcome to the Sentiment Analysis Project repository! This project focuses on analyzing sentiment in textual data using natural language processing techniques.

Project Files

• Data Files:

  • DATA2.json: Sample data file.
  • Data.rdf: Data file in RDF format.
  • data.txt: Text data file.
  • data1.json: Another sample data file.
  • data.spacy: Spacy processed data file.

• Jupyter Notebooks:

  • Data_Feed_Sentiment_Analysis_V1.ipynb: Jupyter notebook for sentiment analysis.
  • Untitled.ipynb: Untitled notebook.
  • Untitled1.ipynb: Another untitled notebook.
  • Untitled2.ipynb: Yet another untitled notebook.

• Python Scripts:

  • pol.py: Python script for sentiment analysis.
  • sentiment_v1.py: Another Python script for sentiment analysis.

Getting Started

To get started with the sentiment analysis project, follow these steps:

1. Clone the Repository:

   git clone https://github.com/aditya2922/sentiment-analysis.git
   cd sentiment-analysis

2. Explore the Notebooks: Open and explore the Jupyter notebooks (Data_Feed_Sentiment_Analysis_V1.ipynb, Untitled.ipynb, etc.) to understand the sentiment analysis process and methodology.

3. Run Python Scripts: Execute the Python scripts (pol.py, sentiment_v1.py) for sentiment analysis on your own data.

Usage

1. Jupyter Notebooks:

   • Open the relevant Jupyter notebook.
   • Follow the instructions within the notebook for sentiment analysis.

2. Python Scripts:

   • Run the Python scripts via the command line or an IDE.
   • Provide input data as required.

Contributing

Contributions to the project are welcome! Whether it's bug fixes, enhancements, or new features, feel free to open issues or pull requests.

License

This project is licensed under the MIT License.

Acknowledgments

Thank you to the contributors and open-source projects that inspired and contributed to this sentiment analysis project.

Feel free to explore, learn, and contribute to the Sentiment Analysis Project!