Fake news related to the coronavirus pandemic has now become a huge problem since false information can lead to worry and concerns regarding the disease. It is not possible to perfectly detect fake news unless the news has been labelled fake or real. Therefore, I have taken this issue as my problem and have developed a project that can detect fake news regarding Covid19 pandemic with the help of the dataset from Kaggle containing Covid19 public media information. I have also used different machine learning classifiers to check which classifier is best suited for the detection
• To detect fake news with the help of sklearn classifiers using confusion matrix and feature words from given Covid19 public media dataset
• To identify the words and token counts that lead to real or fake news
• To compare and analyze different classifiers used and to evaluate the best classifier for detecting the fake news