 This work goes back to really a dramatic moment when the Boston Marathon bombings had occurred in Boston and there was a manhunt underway after the bombings to look for the suspects. We are following developments out of Boston this morning where police are searching for the second Marathon bombing suspect. When the dust settled and the manhunt was over, the solution I compared notes and realized we both had the same experience as many others which was in a near information vacuum from other sources. We were relying heavily on Twitter and other social media to understand what was going on moment by moment. I remember very clearly the lockdown and of course MIT was involved in the incident as well with one of the police officers being shot. That's right. It was right here on campus. And I remember very well my friends and I used Twitter and other social media platforms as one of our main sources of news because usually they were way ahead of traditional news sources and it was after the fact that I realized that a lot of what I was reading during that week was actually rumors, false news and that's why I was really concerned about the effects social media is having on consumers of news. Then if you remember I walked into your office and we talked about changing my PhD direction and focusing on automatically detecting and verifying these rumors that spread on Twitter. I thought it was fantastic because and had a tremendous amount of foresight. Today we're sitting in 2018 talking about veracity, predicting veracity of information flowing online but this was years ago that you had the idea to really study this in depth with sophisticated machine learning to create new types of algorithms for veracity detection and I thought it was one of the best ideas I had heard in a long time. So it was for me a no-brainer to get involved.