Keerthibala T


2024

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KEC_HAWKS@DravidianLangTech 2024 : Detecting Malayalam Fake News using Machine Learning Models
Malliga Subramanian | Jayanthjr J R | Muthu Karuppan P | Keerthibala T | Kogilavani Shanmugavadivel
Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages

The proliferation of fake news in the Malayalam language across digital platforms has emerged as a pressing issue. By employing Recurrent Neural Networks (RNNs), a type of machine learning model, we aim to distinguish between Original and Fake News in Malayalam and achieved 9th rank in Task 1.RNNs are chosen for their ability to understand the sequence of words in a sentence, which is important in languages like Malayalam. Our main goal is to develop better models that can spot fake news effectively. We analyze various features to understand what contributes most to this accuracy. By doing so, we hope to provide a reliable method for identifying and combating fake news in the Malayalam language.