The rapid diffusion of information and opinions through social media, such as web forums and micro-blogs, is affecting the development of crisis situations, such as the Iranian presidential election, the Egyptian protest, and the ROKS Cheonan sinking. Understanding this rapid widespread diffusion, and assessing what information is spreading, what ideas are becoming common, and who is talking about what, is critical for crisis management. This paper presents a computational system for social media assessing the flow of ideas on the web and changes in who is talking about what. This system, given raw social media data, identifies the key topics, the key paths by which topics evolve, the key individuals who contribute to the topic, and the key influence relations between the contributors. We present this system implemented with the Author-Topic model, the meta-network model, and various computational techniques to find and filter the heavy contributors and influences. We demonstrate the performance of the system, by applying it to social media data surrounding the ROKS Cheonan sinking. We describe the results of assessing the initial and changing perceptions of the event using this system.