Identifying limbic characteristics on twitter

Abstract

An adaptive, intelligent system requires certain knowledge of its users. Patterns of behavior, preferences, and motives for decision making must be readily identifiable for the computer to react to. So far, typifying of users needed either a huge collection of empirical data via questionnaires or special hardware to track the user's behavior. We succeeded to categorize users by analyzing only a small amount of the data trace a user leaves while using the online social network (OSN) Twitter. Our approach can be adapted to other platforms easily. Thus, human behavior is made understandable for computer systems and will help to improve the engineering of human-computer-interactions. © 2013 Springer-Verlag.