Fake News Detector

Bonisiwe Shabane

-Dec 2, 2025, 10:58 AM

The media misrepresented President Trump’s call for Members of Congress to be held accountable for inciting sedition by saying that he called for their “execution.” The Democrats and Fake News Media subversively implied that President Trump had issued illegal orders to service members. Every order President Trump has issued has been lawful. It is dangerous for sitting Members of Congress to incite insubordination in the United States’ military, and President Trump called for them to be held accountable. • Democrats released a video calling for service members to disobey their chain of command, and in turn, implied President Trump had issued illegal orders.• President Trump has never issued an illegal order. The Fake News knew that, but ran with the story anyway.

• Video of Democrat Officials Calling for Sedition• Trump accuses Democrats who urged military to resist illegal orders of ‘seditious behavior,’ suggests execution• Trump calls for arrest of ‘seditious’ Democrats who told troops their... A record of the media’s false and misleading storiesflagged by The White House. Scroll for the Truth. This repository contains a comprehensive project for detecting fake news using machine learning techniques and various natural language processing techniques. The project includes data analysis, model training, and a web application for real-time fake news detection. The machine learning model is designed to classify news articles as either real or fake based on their content.

We aim to develop a machine learning program to identify when a news source may be producing fake news. The model will focus on identifying fake news sources, based on multiple articles originating from a source. Once a source is labeled as a producer of fake news, we can predict with high confidence that any future articles from that source will also be fake news. Focusing on sources widens our article misclassification tolerance, because we will have multiple data points coming from each source. The intended application of the project is for use in applying visibility weights in social media. Using weights produced by this model, social networks can make stories that are highly likely to be fake news less visible.

The repository is organized into the following directories and files: A full training dataset with the following attributes: Advanced verification system that accurately identifies real and fake news System scans for suspicious patterns including sensationalism, conspiracy theories, and AI-generated content Multiple factors are considered before classifying content as fake or real Content with specific credibility markers is verified as real

Content is classified based on evidence and patterns, with clear explanations for each decision Cut through the noise and get to the truth. BiasBreak is your AI-powered tool for fact check, fake news detection, and uncovering hidden Bias in any content, helping students, researchers, journalists, and everyday readers make informed decisions instantly. Got a news topic? Verify it with just one click. BiasBreak helps you detect misinformation and bias in seconds using advanced AI and natural language processing.

Just input an article, URL, or text—our system analyzes the content, detect bias, and flags misinformation, giving you a clear trust score and vital insight into its credibility. Simply paste the text you want to analyze or provide the URL of the source you wish to verify. BiasBreak supports both direct input and web-based content. Our advanced AI model processes the content to determine its authenticity, detect bias, analyze sentiment, and assess credibility all in real-time. Within moments, you’ll receive a detailed breakdown of the content’s authenticity score, bias indicators, emotional tone, and credibility level empowering you to make informed decisions. Fake News Detector 101 helps you verify online articles instantly using advanced AI.

Real-time AI analysis that evaluates the accuracy, bias, and reliability of online information — empowering you to read smarter and stay informed, without compromising your privacy. Examines articles for tone and manipulation to flag misleading content. Displays AI-based trust scores instantly while you browse. Highlights credible domains and verified citations. Fake news on different platforms is spreading widely and is a matter of serious concern, as it causes social wars and permanent breakage of the bonds established among people. A lot of research is already going on focused on the classification of fake news.

Here we will try to solve this issue with the help of machine learning in Python. Before starting the code, download the dataset by clicking the link. The shape of the dataset can be found by the below code. As the title, subject and date column will not going to be helpful in identification of the news. So, we can drop these column. Completely in-browser Fake News detection through neural networks.

The "Fake News Detection" Chrome Extension is an innovative tool that harnesses the power of neural networks to help users identify and avoid misinformation while browsing the internet. Unlike other fact-checking tools that rely on external databases or pre-written rules, this extension performs all analysis completely within the browser, ensuring maximum privacy and security for users. With its state-of-the-art neural network technology, the extension can quickly and accurately identify potential fake news articles based on a variety of factors, including the credibility of the source, the use of emotional or... When a potentially misleading article is detected, the extension displays a warning message to the user, along with a detailed explanation of why the article was flagged. One of the best things about the "Fake News Detection" Chrome Extension is that it is completely free to use and does not require any kind of user login or registration. This means that anyone can download and install the extension in just a few clicks and start using it immediately.

Because the extension is entirely self-contained and does not rely on external databases or user data, users can trust that their privacy is always protected. There are no hidden fees or charges, and no personal information is ever collected or shared. Overall, the "Fake News Detection" Chrome Extension is an essential tool for anyone who wants to stay informed while avoiding the pitfalls of fake news and misinformation. Chat with your pages, get tooltips on unverified information, automatic fact-checks, and more. This extension allows users to fight against the threat of fake news by submitting text for predictions through Deep Learning… ChatGPT TextCheck - analyze any text for Influence & Propaganda with AI

A tool developed by Keele University researchers has been shown to help detect fake news with an impressive 99% level of accuracy, offering a vital resource in combatting online misinformation. The researchers Dr Uchenna Ani, Dr Sangeeta Sangeeta, and Dr Patricia Asowo-Ayobode from Keele’s School of Computer Science and Mathematics, used a number of different machine learning techniques to develop their model, which can... The method developed by the researchers uses an “ensemble voting” technique, which combines the predictions of multiple different machine learning models to give an overall score. Impressively, this technique was accurate in identifying fake news 99% of the time, which significantly exceeded the researchers’ predictions and expectations. Their hope is that now the method can be further refined as AI and machine learning systems become more sophisticated, enabling them to eventually produce a model that is 100% accurate at identifying fake...

Fake News Detector

People Also Search

The Media Misrepresented President Trump’s Call For Members Of Congress

• Video Of Democrat Officials Calling For Sedition• Trump Accuses

We Aim To Develop A Machine Learning Program To Identify

The Repository Is Organized Into The Following Directories And Files:

Content Is Classified Based On Evidence And Patterns, With Clear