AI BASED SOLUTION FOR FLAGGING OF FALSE INFORMATION ON ONLINE PLATFORMS

Machine learning is an area of artificial intelligence (AI) and computer science that focus on the use of data and algorithms to mimic the way humans learn over time, gradually improving accuracy. Fake news detection is an important problem in today’s society, as the spread of false information – can have a serious consequence. Social media platforms have become a primary source of news and information for many people, and they have made it easy for users to create and share content. However, this ease of access and sharing has also made it easier for false or misleading information to spread quickly and widely. Fake news is most commonly used to target politicians and respected or business leaders in society. Fake news may be detected automatically using machine learning classification algorithms. This method compares the differences in official information and information shared through social media. The linguistic cue and network analysis approach are the two basic approaches for detecting misleading information. Detecting fake news requires analysing large amounts of textual data for that NLP techniques specifically the TF-IDF method is used to convert news articles into numerical vectors. Machine learning algorithms such as Logistic regression, SVM and K-NN are used to classify the articles as real or fake news.