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Sentiment Analysis for Personalized Chatbots in E-Commerce Applications

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Abstract

Chatbots and question-answering systems aim to provide precise answers to user inquiries, as opposed to simply providing a list of related documents as is typical of traditional search engines. To improve the chatbot’s performance, personalization techniques are employed to deliver customized information to each user based on their interests. Additionally, sentiment analysis techniques are utilized to better understand the user’s queries and emotional state. The goal is to better understand the user and his needs to deliver the required information. In this work, we propose a personalized chatbot enhanced with sentiment analysis features to provide useful and tailored information for each user. The paper details the system’s key components and the techniques employed for handling user queries. To evaluate the effectiveness of our system, we have implemented a proof-of-concept version as customer service chatbot in e-commerce applications. The experimental results obtained based on users’ feedback indicate a significant improvement in user satisfaction with the customized answers and the overall experience. Overall, this system demonstrates the potential of utilizing sentiment analysis in conjunction with personalization techniques to improve the performance and effectiveness of chatbots and question-answering systems.

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Authors and Affiliations

  1. MASI Laboratory, Computer Science Department, Polydisciplinary Faculty, Mohammed First University, Nador, Morocco

    Anas El-Ansari

  2. LAROSERI Laboratory, Computer Science Department, Sciences Faculty, Chouaib Doukkali University, El Jadida, Morocco

    Abderrahim Beni-Hssane

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  1. Anas El-Ansari
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  2. Abderrahim Beni-Hssane
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Correspondence to Anas El-Ansari.

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El-Ansari, A., Beni-Hssane, A. Sentiment Analysis for Personalized Chatbots in E-Commerce Applications. Wireless Pers Commun 129, 1623–1644 (2023). https://doi.org/10.1007/s11277-023-10199-5

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