EngageInsight analyzes user interactions in comment data. It provides insights through visualizations created using Python libraries like Pandas and Matplotlib. The project aims to uncover patterns and trends in user engagement. The visualizations provide an overview of comment lengths and the frequency of different types of replies.
- Data cleaning and preprocessing
- Creation of informative visualizations using Python libraries
- Analysis of user engagement and interaction patterns
To run this project, you need to have Python installed. You can install the required libraries using the following command:
pip install -r requirements.txt- Clone the repository:
git clone https://github.com/Yash22222/Data-Analysis-on-Real-Time-Social-Media-Comments.git- Navigate to the project directory:
cd Data-Analysis-on-Real-Time-Social-Media-Comments- Run the Jupyter Notebook or Python script to analyze the dataset and generate visualizations:
jupyter notebook DA_RT_SMD.ipynbContributions are welcome! Please open an issue or create a pull request if you have suggestions or improvements.
This project is licensed under the MIT License.
This README provides clear instructions for installation, usage, contributing, and licensing, with properly formatted command code blocks. Feel free to use this as a template for your project!