Predicting Twitter trends can be done hours before Twitter does, at least according to one researcher from MIT. Associate Professor Devavrat Shah says he has created an algorithm that can identify Twitter trends hours before the service can. The real value of this model might not be helping Twitter, but in helping businesses use predictive analytics more effective. Here is how it works: an algoritm compares real-time data with historical data and predicts outcomes based on past events that most closely align with the current situation. So, in stead of analyzing a topic’s chances of trending equally against the entire historical corpus of topics, it will assign more weight to topics whose paths followed similar trajectories up the ranks of top trends. According to a release from the MIT News Office the model was 95 percent accurate during testing and has been predicting trends hours before they appear on Twitter’s list The most interesting part of all this is that there are potentially more lucrative and rewarding endeavors that could benefit from this type of predictive power. Shah himself suggests stock markets, movie ticket sales and public transportation as possibilities, but why stop there. We could see similar tools or applications for identifying threats earlier or predicting the severity of disease outbreaks. But businesses could also hugely benefit from identifying trending topics within a specific target group or market segment. From a business perspective: what kind of trending topics would help you make better decisions? You can read more on predictive analytics in our report on Big Social.