iamaziz/ar-embeddings
Sentiment Analysis for Arabic Text (tweets, reviews, and standard Arabic) using word2vec
Implements document-level sentiment classification by converting tokenized Arabic text to dense vectors using pre-trained word2vec embeddings (159K vocabulary, 300 dimensions trained on news corpora), then evaluates multiple scikit-learn classifiers (LinearSVC, LogisticRegressionCV, etc.) on benchmark datasets like LABR book reviews. Includes pre-computed Arabic embeddings and standardized train/test splits, enabling reproducible sentiment classification across formal and informal Arabic text variants.
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95
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48
Language
Python
License
MIT
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Last pushed
Aug 20, 2024
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