Self-Adapting Chatbot Personalities for Better Peer Support

Studies have shown that people relate better with other people who have similar personality characteristics as themselves. This is helpful in peer support scenarios where people should be receptive to receiving support and advice from others. In this paper we propose a chatbot personality model and an algorithm that enables the chatbot to adapt its personality in real-time as it interacts in conversation with the user. Our model is based on the Big Five personality model and we focus on two key personality traits, Extroversion and Agreeableness. The personality adaption algorithm uses an interactive genetic algorithm. We have exposed the chatbot to a controlled set of interactions and a user and the results show that the algorithms are capable of adapting personality traits to match the identified traits of the user. In the next phase of our experimentation we will expose the chatbot to healthcare professionals.

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