Web — social media is commonly assumed to be culpable for this growth, with ‘the news’ and current affairs deemed the epicentre of the battle for information credibility. This review begins by explaining the key definitions and discussions of the subject of fake news, and online misinformation and disinformation with the aid of each book in turn. Web — fake news detection taxonomy was proposed in this research. Web — in this paper, we provided a benchmark framework in order to analyze and discuss the most widely used and promising machine/deep learning techniques for fake news detection, also exploiting different features combinations w. r. t. The ones proposed in. Web — the main purpose of this work is to analyse the current state of knowledge in detecting fake news; On the one hand to show possible solutions, and on the other hand to identify the main challenges and methodological gaps to motivate future research. Previous article in issue. Next article in issue. Web — fake news detection is a subtask of text classification [ 1] and is often defined as the task of classifying news as real or fake. The term ‘fake news’ refers to the false or misleading information that appears as real news. Webfake news detection is a subtask of text classification [1] and is often defined as the task of classifying news as real or fake. The term ‘fake news’ refers to the false or misleading information that appears as real news. It aims to deceive or mislead people. Webtruth detector is an innovative software solution empowering users to distinguish between real and fake news. Web — extensions like newsguard, trustservista, media bias/fact check, and the factual integrate into your browser and display grades, rankings, and reports to tell you more about the news sources you. Web — one direct application of this would be embedding the model into a news app like apple news. This would give the user a live analysis of each article in their news feed and inform them of any potential biases (e. g. “this article has a 43% chance of having moderately liberal bias”) before they even have to click on anything!
