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Twitter Sentiment Analysis using Python 🐍 and NLP 📙

🚀 Project Overview

Welcome to the Twitter Sentiment Analysis project! 🌟 Here, we dive into the captivating realm of Natural Language Processing (NLP) to analyze tweet sentiments using mighty machine learning techniques.

📊 Dataset

Access the dataset here: Sentiment140 Dataset. 📂

🛠️ Methodology

We wield the power of classifiers to craft an effective sentiment analysis model, evaluating their prowess with accuracy and F1 scores. 🔍

Getting Started 🏁

Follow these simple steps to set up and start working on the project:

  1. Clone the Repository:

    git clone https://github.com/labrijisaad/Twitter-Sentiment-Analysis-with-Python.git

  2. Navigate to the Project Directory:

    cd Twitter-Sentiment-Analysis-with-Python

  3. Check Python Version: Ensure that you have Python 3.9 installed. You can find the required packages in the requirements.txt file.

  4. Create a Virtual Environment (recommended for project isolation):

    python3 -m venv venv

  5. Activate the Virtual Environment:

    • For macOS/Linux:

      source venv/bin/activate

    • For Windows:

      venv\Scripts\activate

  6. Install Dependencies from requirements.txt:

    pip install -r requirements.txt

  7. Download the Dataset: Download the dataset from Sentiment140 Dataset and place the CSV file in a newly created data directory within the project.

  8. Launch Jupyter Notebook: Start the Jupyter Notebook server:

    jupyter notebook

🙏 Acknowledgments

This project was inspired by the helpful work of analyticsvidhya. 🎩🙌

📞 Contact

For any queries, suggestions, or virtual high-fives, feel free to reach out at [email protected]. 📬