Mesay Yigezu


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Habesha@DravidianLangTech 2024: Detecting Fake News Detection in Dravidian Languages using Deep Learning
Mesay Yigezu | Olga Kolesnikova | Grigori Sidorov | Alexander Gelbukh
Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages

This research tackles the issue of fake news by utilizing the RNN-LSTM deep learning method with optimized hyperparameters identified through grid search. The model’s performance in multi-label classification is hindered by unbalanced data, despite its success in binary classification. We achieved a score of 0.82 in the binary classification task, whereas in the multi-class task, the score was 0.32. We suggest incorporating data balancing techniques for researchers who aim to further this task, aiming to improve results in managing a variety of information.