Detection of Rumors in Social Network Based on Machine Learning Algorithm

In this time many people who use smartphones like to read news online on social media platforms. There are various ways to give the news. The problem is determining how to verify the facts and stories that are scattered across social media websites like Facebook Pages, WhatsApp Groups, and Twitter. People should not consider such claims and should not act as though they believe the information to be true. This paper discusses method for detection of rumors in social network. The desire is to stop spreading rumors, especially in a developing nation like India, and focus on reporting accurate news. A model for identifying bogus news is provided in this manner. In order to create a classifier that can draw conclusions about data based on the corpus's content and utilize a text classification method, employing a classification model, and investigate the results, we are using a corpus of labelled true and fake news items. In this research paper we have used decision tree with 99.63 percent accuracy.