Today, social media platforms have become almost a normal place in our lives, and we need to secure and give users a clear picture of the apps we are creating. Furthermore, hate speech and fake news are increasingly circulating more and more on platforms despite surveillance efforts made by platform hosts. This work is designed to spot hate speech and fake news on social media platforms using information extracted from user-generated content. Relevant information provided to users will help address the research question, and a modified version of Twitter will be developed to show the importance of this system functioning on a particular data collection and later, the findings of this system will be discussed.