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twitter-based-sentiment-analysis-russia-ukraine-conflict

https://github.com/durgesh1029/twitter-based-sentiment-analysis-russia-ukraine-conflict

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
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    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (14.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: Durgesh1029
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 7.97 MB
Statistics
  • Stars: 1
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 7 months ago · Last pushed 7 months ago
Metadata Files
Readme Citation

README.markdown

DM Project Repository

Overview

This repository contains the implementation of the DM Project as outlined in the DM_project(2)(1).pdf document. The project focuses on [assumed objective, e.g., data mining tasks such as classification, clustering, or association rule mining]. The codebase is written in Python and includes scripts for data preprocessing, analysis, and visualization.

Repository Structure

DM_project/ ├── data/ # Directory for datasets (not included in GitHub due to size/privacy) ├── src/ # Source code │ ├── preprocess.py # Data preprocessing script │ ├── analysis.py # Main analysis or modeling script │ └── visualize.py # Visualization script ├── docs/ # Documentation │ └── requirements.txt # Project dependencies ├── notebooks/ # Jupyter notebooks for exploratory analysis │ └── exploration.ipynb # Sample notebook ├── README.md # Project overview (this file) └── .gitignore # Git ignore file

Setup Instructions

  1. Clone the repository: bash git clone https://github.com/yourusername/dm_project.git cd dm_project
  2. Install dependencies: Ensure Python 3.8+ is installed, then run: bash pip install -r docs/requirements.txt
  3. Prepare data: Place your dataset(s) in the data/ folder as specified in the PDF.
  4. Run the scripts: Execute the main analysis script: bash python src/analysis.py

Dependencies

See docs/requirements.txt for a list of required Python packages (e.g., pandas, scikit-learn, matplotlib).

Usage

  • Run preprocess.py to clean and prepare the data.
  • Run analysis.py to perform the main data mining tasks.
  • Use visualize.py to generate plots and visualizations.
  • Explore notebooks/exploration.ipynb for interactive analysis.

Notes

  • The data/ folder is excluded from version control. Ensure you have the datasets referenced in the PDF.
  • Update this README with specific project objectives or tasks from the DM_project(2)(1).pdf file.

Contributing

Feel free to submit issues or pull requests for improvements.

License

This project is licensed under the MIT License.

Owner

  • Name: Durgesh Dongre
  • Login: Durgesh1029
  • Kind: user
  • Location: Kanpur
  • Company: IIT Kanpur

⚡ I’m an electrical engineer passionate about combining power systems with AI 🤖, machine learning 📊, and deep learning 🧠 to solve real-world problems.

Citation (CITATION.md) 

I have used or reference the work on sentiment analysis of Twitter data regarding the Russia-Ukraine conflict in your project, please cite the following paper:

Chaudhry, M., Prakash, N., Patel, N., Abhis, Kumar Patel, H., & Mishra, D. K. (2025). Analyzing Sentiments in Twitter Data on Russia-Ukraine Conflict Using Machine Learning Methods. 2025 2nd International Conference on Computational Intelligence, Communication Technology and Networking (CICTN).

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