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⚠️ Note

This project was originally developed in 2019. Some libraries, APIs, and functions used in the code may now be deprecated or updated.

It is recommended to use this repository primarily to understand the overall workflow, feature engineering techniques, and modeling approach.

For practical use, please update the dependencies and modify deprecated functions to align with the latest versions of the libraries.

🧠 NLP Techniques Used

The following NLP techniques are used for feature extraction:

  • Bag of Words (BoW)
  • TF-IDF
  • Word Embeddings
    • Word2Vec
    • Doc2Vec

📌 Each of the below classification algorithms has been trained and evaluated on all of the above NLP techniques.


🤖 Classification Algorithms

  • Logistic Regression
  • Support Vector Machine (SVM)
  • Random Forest
  • Extreme Gradient Boosting (XGBoost)
  • Light Gradient Boosting (LightGBM)

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Benchmarking multiple ML models in combination with diverse NLP approaches for Twitter sentiment analysis

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