Abstract:
Fake news is information that’s reported to be false or misleading information which spreads through social media, and poses a serious threat to our society. Much of the work is done already and the tool are publicly available and could be used by journalists to fact-check their stories before publishing or by readers to verify the information they read. The main focus of this project is to design and develop a web-based system in multiple languages to detect fake news using Natural Language Processing techniques. We propose a classification model that is a model capable of detecting fake news based on Word2vec embedding as a feature extraction method. The document is structured as follows in Chapter 1, an introduction of the project in detail. Chapter 2 detailed the description of the existing models. In Chapter 3, the requirements for the system to be developed are presented and discussed in regard to the performance of the ML systems. Conclusions are mentioned in the last Chapter
