In this project we examine the social media and traditional media's response to the Boston Marathon bombings from the moment of the explosion to two weeks after the events, including the search, hunt, and capture of the suspects. We use big data analytics, natural language processing, and complex system and network analysis techniques. We focus specifically on information flow, engagement and attention of the audience, emergence of broadcasters, source and spread of rumors, and interplay of various media. We hope to develop a better understanding of the nature of information generation and flow from broadcasters and audiences across different media. Using this event as a case study, we can find out what went wrong or right, and come up with recommendations for different actors (news sources, social media participants, police departments) to better facilitate information flow and minimize misunderstanding and the spread of false information.