Communicating with Machines: Conversational Agents with Personality and the Role of Extraversion

Abstract

Communication with conversational agents (CA) has become increasingly important. It therefore is crucial to understand how individuals perceive interaction with CAs and how the personality of both the CA and the human can affect the interaction experience. As personality differences are manifested in language cues, we investigate whether different language style manifestations of extraversion lead to a more anthropomorphized perception (specifically perceived humanness and social presence) of the personality bots. We examine, whether individuals rate communication satisfaction of a CA similar to their own personality as higher (law of attraction). The results of our experiment indicate that highly extraverted CAs are generally better received in terms of social presence and communication satisfaction. Further, incorporating personality into CAs increases perceived humanness. Although no significant effects could be found in regard to the law of attraction, interesting findings about ambiverts could be made. The outcomes of the experiment contribute towards designing personality-adaptive CAs.