Uma abordagem para aumento de empatia das interações textuais em sistemas colaborativos

Abstract

Empathy plays an essential role in social interactions, for example, in effective teaching-learning processes in teacher-student relationships, and in the company-client or employee-customer relationships, retaining potential partners and providing them with greater satisfaction. In parallel, Computer-Mediated Communication (CMC) support people in their interactions, especially when it is necessary to circumvent space-time limitations. In CMC, there are several approaches to promote empathy in social or human-computer interactions. However, for this type of communication, a little explored mechanism to gain empathy is the use of the theory of Neurolinguistics that presents the possibility of developing a Preferred Representation System (PRS) for cognition in humans. In this context, this work presents the conception and results obtained through the experimental evaluations of the NeuroMessenger library, that uses Neurolinguistics, Psychometry and Text Mining to promote empathy among interlocutors, from the PRS identification and suggestion of textual matching based on this classification. The results showed that the use of the same text pattern (PRS) increases the empathy among the interlocutors of Collaborative Systems, evidencing that the matching feature can significantly improve the communication and construction of rapport in virtual environments.