Authorship analysis design framework. Web forum pages are collected, with relevant data extracted and archived in a database. Features are generated from author messages, which are used for both author feasibility testing. Extreme authors are chosen based on affect analysis; identified authors are then tested for their feasibility in this experiment, as not all authors have unique writing styles. Authorship analysis is then performed using a decision tree classifier. Test results are then evaluated.