May 8, 2019 · Our results reveal interesting findings on the usefulness and importance of features for detecting false news. Finally, we discuss how fake news ...

The AUC is especially relevant for fake news detection since the decision threshold can be used to control the tradeoff between true and false positive rates.

Jul 8, 2024 · This research explores the effectiveness of supervised learning and reinforcement learning models in detecting fake news, which is a growing concern in the ...

Our results reveal interesting findings on the usefulness and importance of features for detecting false news. Finally, we discuss how fake news detection ...

Topics · Domain Location · Fake News · Fake News Detection · False News ...

The aim of this research is to detect fake news using deep learning techniques. The method is based on a semi-supervised learning framework targeting both ...

Researchers are using different algorithms to detect the false news. Researchers in (Wang, 2017) said that fake news detection is big challenge. They have used ...

Fake news, formerly defined as a form of news that consists of misinformation or hoaxes. It can spread through different channels such as print and broadcast ...

The study uses machine learning algorithms to detect fake news. By systematically exploring and evaluating various machine learning models, the research ...

Sep 10, 2024 · A lot of research is already going on focused on the classification of fake news. Here we will try to solve this issue with the help of machine learning in ...