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Communication Dans Un Congrès Année : 2020

Measuring the Polarity of Conversations between Chatbots and Humans: A Use Case in the Banking Sector

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Djamel Mostefa
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Résumé

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.
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Dates et versions

hal-03613414 , version 1 (23-03-2022)

Licence

Paternité - CC BY 4.0

Identifiants

Citer

Guillaume Noé-Bienvenu, Damien Nouvel, Djamel Mostefa. Measuring the Polarity of Conversations between Chatbots and Humans: A Use Case in the Banking Sector. 15th Federated Conference on Computer Science and Information Systems (FedCSIS 2020), Sep 2020, Sofia, Bulgaria. ⟨10.15439/2020f63⟩. ⟨hal-03613414⟩
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