How does DeepCheck work?

DeepCheck detects fake news by extracting linguistic characteristics from a large body of news articles. It takes a piece of text and identifies the frequency of specific words commonly used in fake news articles and compares it on the similarity to real news items that it has analyzed before.

Spotting and mitigating fake news

DeepCheck identifies linguistic characteristics to spot fake news using machine learning and natural language processing technology. Our research on a large collection of fact-checked news articles, science journals and white papers on a variety of topics regarding COVID-19 shows that, on average, fake news articles use more words related to sex, death and anxiety. Many expressions used are also common in hate speech. We assume that a linguistic and stylistic approach combined with machine learning is useful in spotting misleading information and suspicious news.