Automated detection of fake news

During the last decade, social media has been regarded as a rich dominant source of information and news. Its unsupervised nature leads to emergence spread fake Fake news detection gained great importance posing many challenges research community. One main is accuracy which highly affected by chosen extracted features used classification algorithm. In this paper, we propose context based solution that relies on account random forest classifier detect It achieves precision 99.8%. The system compared other commonly classifiers such decision tree classifier, Gaussian Naïve Bayes neural network give 98.4%, 92.6%, 62.7% respectively. experiments’ results show possibility distinguishing giving credibility scores for with relatively high performance.