abdulfatir/twitter-sentiment-analysis resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1653 stars · 602 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Python scripts comparing sentiment analysis methods on tweets, including Naive Bayes, SVM, logistic regression, CNN, and LSTM models built with scikit-learn and Keras. It was a course project, is archived, and cannot ship its dataset due to copyright restrictions.

Use cases

• classify tweets as positive or negative
• compare classical and deep learning models for sentiment classification
• learn how to preprocess Twitter data for NLP
• implement LSTM and CNN text classifiers in Keras
• study a sentiment analysis project report with results

When to choose

• you want reference implementations of multiple sentiment classifiers to study or adapt
• you need a starting point for tweet preprocessing and feature extraction
• you are learning NLP classification techniques with worked examples

When to avoid

• you need a maintained production-ready sentiment analysis library
• you expect the original Twitter dataset to be included
• you need support for recent Python, TensorFlow, or Keras versions without modifications

Facets

learning-resource · maturity abandoned

machine-learning nlp deep-learning machine-learning social-media python sentiment-analysis twitter lstm cnn naive-bayes svm keras course-project archived natural-language-processing

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