Social Media has become an important source for information about people and real-world events. Its importance is driven largely by the enormous number of people generating and updating content in Social Media platforms. In this report, we measure the extent to which we can accurately measure the salience of topics/concepts that might be of interest to an analyst, and evaluate whether concepts like positive and negative sentiment can be meaningfully extracted from Social Media content. As a test case, we examined Twitter content generated by female users who are sympathetic to the Islamic State in Iraq and Syria (ISIS). The basic technique proposed here can be developed further to create a more fine-grained exanimation of Social Media content.