Measuring the Polarity of Conversations between Chatbots and Humans: A Use Case in the Banking Sector
Guillaume Le Noé-Bienvenu, Damien Nouvel, Djamel Mostefa · Annals of Computer Science and Information Systems · 2020
This paper describes a study on opinion analysis applied to both human to chatbot conversations, but also to human to human conversations using data coming from the banking sector.A polarity classifier SVM model applied to conversations provides insights and visualisations of the satisfaction of users at a given time and its evolution.We conducted a study on the evolution of the opinion on the conversations started with the chatbot and then transferred to a human agent.This work illustrates how opinion analysis techniques can be applied to improve the user experience of the customers but also detect topics that generate frustrations with a chatbot or with human experts.