In news media, echo chambers refer to situations in which information is amplified or reinforced by communication and repetition. The characteristic of an echo chamber is, therefore, the absence of controversial discussions and a narrow set of opinions about a topic. We propose the use of Visual Analytics to describe spatiotemporal distributions of echo chambers using Twitter data, for specific geolocated events, such as concerts, strikes, demonstrations, etc. We analyze the echo chambers for Boston Marathon Bombing that took place on April 15, 2013. The social groups are displayed by a matrix view containing all connected components of the tweet mention graphs. To identify similar opinions, as well as, the diversity of topics in a discussion, we apply text classification and sentiment analysis. Lastly, we present initial findings based on real-world data.