Fake News: Stanford Student Aims To Identify False Sites With Neural Networks

In the wake of the 2016 election, marred by questions of the influence of fake news, the biggest presences on the web have been tasked with figuring out ways to stop the spread of false information. While those companies are at work on their own solutions, Stanford student Karan Singhal believes he has a better answer. The 19-year-old computer science major is taking as much of the human element out of the process of fake news detection as possible with Fake News Detector AI --a website and Google Chrome extension designed to sniff out fake news sites. To accomplish the task, Singhal is employing neural networks--a sort of artificial brain that can process a number of factors at a time, weighing each element and producing a verdict on the validity of a particular website. Instead of tasking people with fact checking individual claims or trying sort between bias and outright falsehoods, the Fake News Detector AI goes under the hood of a website in question and examines its parts, which can be more revealing than the text on the screen. Singhal told IBTimes his algorithmic method sorts over site layout, popularity, writing style, the frequency of telling keywords like "liberal" and "conservative," among other aspects of a given site.