It was the intersection between social media data and finance that got Northeastern senior Daniel Bostwick hooked. He had already completed a coop at Intuit and served as a software developer for both Bloomberg and Buzzient. Up next? SocialTradr — his way of bringing social media analytics to financial professionals.

SocialTradr uses data mining algorithms to collect public opinion from various social media networks, such as Facebook, Twitter and Reddit, as well as blogs and online news sources. That data is then sent through SocialTradr’s proprietary real-time analytics system to generate actionable data points, essentially quantifying public opinion.

“The most obvious implication of analytics is marketing, but I think that’s saturated at the moment,” Bostwick says, referring to the reason why SocialTradr is focused more on finance. What he wanted to be able to do, however, was something Google referenced in a paper years ago: “Predict the present.”

“When you have such a massive conversation happening, you can monitor those conversations, begin to detect trends and patterns and then analyze those conversations,” Bostwick admits, claiming he wants to deliver those analytics to traders and investors and “predict the present” through SocialTradr.

SocialTradr participated in Northeastern’s Husky Startup Challenge, which Bostwick says helped him explore the resources available to his team, comprised of a friend and his brother. The team’s also applied to MassChallenge, and has been encouraging their peers to vote for them. If accepted into MassChallenge, Bostwick says he’ll be able to work on the company full-time.

SocialTradr is currently partnered with an equity research group, and is using them as their first customer to really shape what it is they’re doing. Right now, the team’s looking at charging a monthly subscription rate that traders and investors would have to pay to access. “People in finance might want to watch out for companies or trends, while those in politics can watch for candidates,” Bostwick says.

Could this lead to better predictions on Wall Street? If that’s the case, sign us up.