We're Tweet-Mood, a web based, geolocated sentiment analysis application using live tweets posted in the US. Our goal was to create a more powerful tool for understanding how various socioeconomic and other demographic factors play into the overall sentiments expressed in a community. Our application is built on a python flask server hosted on an AWS ec2 instance. Data is streamed through a redis backed ElastiCache to a naive Bayes classification model. Frontend data visualization is done in LeaftletJS and Mapbox.