For the web’s biggest companies — including not only Twitter and Facebook but Amazon and Google — this ever-expanding online discourse is a treasure trove, a collection of personal information that can help them better understand who you are and, ultimately, get you in front of stuff you want to buy. But this is easier said than done. Their ability to mine all that data hinges on how well their computer algorithms can understand what you’re saying. And let’s face it, machines aren’t too good at that.

But a new algorithm developed at Stanford University could help change this reality, giving computers the power to more reliably interpret language. Called Neural Analysis of Sentiment — or NaSent for short — the algorithm seeks to improve on current methods of written language analysis by drawing inspiration from the human brain.

NaSent is part of a movement in computer science known as deep learning, a new field that seeks to build programs that can process data in much the same way the brain does. The movement began in the academic world, but it has since spread to web giants such as Google and Facebook.