The rise in fake news across the world has slapped the face of journalism. News now available on various platform such as websites and social media has become more susceptible to tampering of the news. Fake news has caused lot of trouble in recent years, providing misinformation to millions of readers. In order to curb this, The University of Michigan researchers have developed a unique algorithm system which is known to detect a fake news better than a human.
A system based on algorithm which can identify telltale linguistic signs in fake news stories is likely to offer news agencies and social media sites to fight against these wrong information. In a recent studies it has been found that these algorithm system was able to detect fake news 76% of the time in comparison to that of human who detected 70% of the fake news. The linguistic analysis approach can also be used to detect fake news which are published recently and cannot be detected with the help of cross referencing their facts with different stories.
It has been found that catching wrong news which is expected to cause a massive impact on the readers is difficult job. Most of the news agency and social media sites completely depend on human editors, who fail to keep up with the pace at which news are published. Current debunking techniques which are often used for checking stories, often uses verification of facts externally which is surely going to be the biggest challenge for newest stories. It has been found that often the damage has been done on the reader by the time the story is proven fake