A proposed machine learning framework and expanded use of blockchain technology could help counter the spread of fake news by allowing content creators to focus on areas where the misinformation ...

Researchers found that integrating emotional features, particularly negative emotions, into machine learning models enhances the accuracy of fake news detection on social media platforms. This ...

The proposed machine learning framework, a division of artificial intelligence (AI), aims to utilize data and algorithms to identify signs of misinformation and enhance the detection process.

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm ... non-machine ...

As a result, NLP greatly extends the capabilities and effectiveness of machine learning. The Deepfake Challenge Then, there is the “most entertaining” fraud of them all: deepfakes.

Detecting misinformation. Detecting misinformation can be done by a combination of algorithms, machine-learning models and humans. An important question is who is responsible for controlling, if ...

Fake video and audio might once again be poised to corrupt the most basic ways in which people process reality—or what’s left of it. So far, deepfakes have been limited by two factors baked ...

That was not the first use of a deepfake to create misleading videos, and tech-savvy political experts are bracing for a future wave of fake news that features convincingly realistic deepfakes.

Controlling the spread of fake news may, in some instances, be considered censorship and a threat to freedom of speech and expression. Even a human may have a hard time judging whether information ...