"Fake News Detection System" Kit by Nishu Kumari

I have created this solution as a part of the 24hr AI challenge. I have used the base kandi kit for fake news detection and train the dataset on political dataset. This solution will help the user to validate whether the news is fake or real and for this i used political dataset. A type of yellow journalism, fake news encapsulates pieces of news that may be hoaxes and is generally spread through social media and other online media. This is often done to further or impose certain ideas and is often achieved with political agendas. Such news items may contain false and/or exaggerated claims, and may end up being viralized by algorithms, and users may end up in a filter bubble. So, to solve this problem i have build a model that accurately classify a piece of news as REAL or FAKE. For training my model i used a political dataset. Using sklearn, we build a TfidfVectorizer on our dataset. Then, we initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares. Implemented a TfidfVectorizer, initialized a PassiveAggressiveClassifier, and fitted my model. I ended up obtaining an accuracy of 93.21% in magnitude. I have also added a demo link on https://drive.google.com/file/d/1U3BsAfd9zWifgbpH6zOOyYd_23TbSpbr/view?usp=sharing