Ideally, debates are like fuel for the engine of democracy. But in their current form on social media, are they really getting us anywhere?
Northeastern professor Lu Wang believes that the right mix of linguistic analysis, artificial intelligence, and data visualization can produce more meaningful debates. Understanding what makes a persuasive argument is at the heart of an interdisciplinary project she is leading. The ultimate goal is to help social media platforms evolve from echo chambers full of hate speech to places where constructive conversations flourish.
“Debates should be mechanisms for discovering something new about the world,” said Nick Beauchamp, assistant professor of political science at Northeastern and a collaborator on the project. “The hope is that you would come away from a debate not with just a set of new facts you learned, but also with a better way of thinking about the problem.”
With this goal in mind, Wang and Beauchamp designed an algorithm that identifies features of a strong argument. Using a dataset of 118 Oxford-style debates—in which the winner is whomever can sway more of the audience to their side—the algorithm was able to predict debate winners 74 percent of the time.
