The research shows promising signs that conversational forecasting methods within the field of natural language processing could prove useful in helping both moderators and users proactively lessen vitriol and maintain healthy, productive debate forums. "Well-intentioned debaters are just human. In the middle of a heated debate, in a topic you care about a lot, it can be easy to react emotionally and only realize it after the fact," said Jonathan Chang, a doctoral student in the field of computer science. The idea is not to tell users what to say, Chang said, but to encourage users to communicate as they would in-person. The tool, named ConvoWizard, is a browser extension powered by a deep neural network.

The past decade has seen lightning-fast evolution in the possibilities of predictive analytics. Given the right data, machine learning (ML) algorithms can make forecasts much more accurately than a human expert. Even experienced high-level executives should be using those insights to inform their business decisions. This level of insight would not only make those decisions more accurate -- it would save executives an enormous amount of time. According to Accenture research, some organizations that deploy ML solutions see a tenfold (or more) increase in time savings.