The Mood-State Indicator (MSI) is an algorithm based on a computational method for predictive linguistics. MSI was developed to explain mental processes underlying human speech and writing in order to predict states of mind and cognition (Howard & Guidere, 2011).
The MSI algorithm deciphers language by breaking down spoken sentences into words, starting from an initial state value and transitioning through successive states. Its function is to accurately detect the state of mind of an individual based on spoken discourse and written sentences (Howard & Guidere, 2011; Howard & Guidere 2012).
This computational linguistic approach to cognitive states rejects the traditional separation between language, thoughts and feelings. The application of this methodology has been clinically utilized to successfully identify various psychological states, such as depression (Howard & Guidere, 2011). By executing this mechanism and correlating our computational data to results calculated by a psychological assessment testing, we are better positioned to classify a patient’s cognitive state.