The importance of detection of fake news is essential in today's times where rumors travel faster via social media. Implement a ML based solution for detection of such rumors and implement a data mining system for dynamic scanning and labeling of news articles and social media posts. The solution should support widely used languages along with ability to let the user provide their own data for retraining and improvising the predictions
To solve above mentioned problem, I built a ML based model which detects and labels the questioned news as fake or real. This system can also be used to retrain the model using dynamic labeling that helps users to use this for further training purposes and improve it's predictions. The model also supports multiple languages and labels them. Taking it further, the user can read the real news related to the questioned news. For social media model, I integrated the model with Twitter bot allowing users to tag the model username (@AppsoluteNerd) with the news and verify it as real or fake.
NumPy, pandas, Translator, News API, Twitter API