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Fake News Detection Using Transformer Model by sowravnath05102002 is a document available to read on EtoBox.

What is Fake News Detection Using Transformer Model about?

This conference paper presents a novel content-based approach for detecting fake news using a transformer model, specifically applied to a COVID-19 dataset. The proposed hybrid model incorporates various features such as sentiment analysis, hate speech detection, and topic modeling, achieving an accuracy of 87% compared to standard baselines. The study also introduces a new Persian-labeled dataset for enhanced analysis of misinformation during the pandemic.

Author
sowravnath05102002
Language
EN