DETECTING MIS-INFORMATION ON SOCIAL MEDIA USING MACHINE LEARNING
Jainam Gandhi, Janvi Godhania, Bharat Gupta, Ashwini Deshmukh · Journal of Emerging Technologies and Innovative Research · 2021
Due to social media people are becoming more exposed to the fake news. It promotes the spread of negativity in the society. Thus fake news detection is becoming one of the major part of the IT industry. Fake news Detection is the non-trivial task, which requires multi-source information such as news content, social context, and dynamic information. Fake news cannot be detected simply based on news contents. In addition to news content, user engagement and social behaviour should also be explored. For example a credible users signal that “this is a fake news” is enough to determine the authenticity. Certain other information like social behaviour of news , the way it has been used by user etc are also important factors. Thus Dataset which contain news content, social context and dynamic information could help in fake news detection. So In our system we provide a way to user in which fake news can be detected. The system uses data mining which provides a way to user to easily detect fake news by using various data mining algorithms