twitter-sentiment-analysis and Twitter-Sentiment-Analysis-
These are ecosystem siblings—both are independent educational implementations of the same sentiment analysis pipeline (Naive Bayes, SVM, LSTM) applied to Twitter data, rather than tools designed to work together or compete for the same use case.
About twitter-sentiment-analysis
abdulfatir/twitter-sentiment-analysis
Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.
Implements a comprehensive comparative framework supporting 10+ classification algorithms (Naive Bayes, SVM, Decision Trees, Random Forest, XGBoost, Logistic Regression, MLP, LSTM, CNN) with standardized CSV input/output format and optional bigram feature extraction. Includes preprocessing pipelines using NLTK for text normalization and frequency distribution analysis, with Keras/TensorFlow backends for deep learning models and scikit-learn for traditional classifiers. Supports ensemble methods through majority voting and CNN feature extraction for downstream SVM classification.
About Twitter-Sentiment-Analysis-
soham2707/Twitter-Sentiment-Analysis-
This is a project of twitter sentiment analysis using machine learning(Support Vector Machines,Naive Bayes), deep learning(LSTM), Transformer(BERT,ROBERTA).
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