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Communication dans un congrès

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

Abstract : 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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Communication dans un congrès
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https://hal-inalco.archives-ouvertes.fr/hal-03613414
Contributeur : Damien Nouvel Connectez-vous pour contacter le contributeur
Soumis le : mercredi 23 mars 2022 - 11:48:09
Dernière modification le : lundi 28 mars 2022 - 10:30:17
Archivage à long terme le : : vendredi 24 juin 2022 - 18:08:43

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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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