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This study presents a hybrid feature fusion and stacking ensemble approach for detecting deepfake text, combining TF-IDF lexical features with Sentence Transformer embeddings to enhance detection accuracy while maintaining computational efficiency. The proposed method achieves an F1-score of 0.9976 across multiple datasets (LIAR, ISOT, and FakeNewsNet) and demonstrates robustness in cross-domain evaluations. The architecture utilizes a lightweight stacking ensemble of Logistic Regression and LightGBM, ensur

Author

deepanjali.100311

Language

EN