{'fraction_non_alphanumeric': 0.017264276228419653, 'fraction_numerical': 0.005312084993359893, 'mean_word_length': 4.844961240310077, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
MYTHYA: Fake News Detector, Real Time News Extractor and Classifier

Fake news is a kind of exploitative journalism which is completely deprived of facts. It spreads disinformation, lies or hoaxes by means of traditional print media, televisions or radio media and nowadays through social media. The spreading of fake news on social media has changed the course of elections and thus impacted the future. Automating fake news detection is essential to maintain the integrity of news and journalism. In this Paper, a system that uses Gradient Boosted Decision Tree and Convolutional Neural network is provided to detect the stance of the news headlines and classify them as real or fake. By combining these two models systems gets the accuracy of 97.59%.