C Becomes The Most Popular Language for "Machine Learning" Fake News Detection

Abstract

Nowadays political people or other people are spreading fake news for their own benefit. Ordinary people easily believe these fake news. As a result, riots are spreading among the people across the country which is risky for a developing country. In this paper, we are working to detect fake news and provide a model for checking fake news. We collected our dataset which has different type of news and labeled them as 0 and 1, which means true and fake respectively. For detecting the fake news we use Long Short-Term Memory, Bidirectional Long-Short Term Memory and Random Forest algorithms in our dataset and compared the results among these model for checking which one gives us a better result. After our experiment we found that Random Forest algorithm had 87.75% accuracy to detect the fake news.