AI Assisted Customer Review Sentiment Analysis and Department Classification Tool

Sentiment analysis is a crucial technique in electronic commerce as it enables businesses to understand customer opinions and emotions about products or services. By analyzing customer reviews, a company can enhance a product or service, improve customer satisfaction, adjust marketing strategies, and even increase sales by addressing negative comments. Accordingly, this study proposes an artificial i ntelligence integrated Python application to perform sentiment analysis on customer reviews to determine whether the review is positive, neutral, or negative. Moreover, a department classification m odel is also proposed to match each customer review to its potential department, such as logistics, sales, etcetera. For evaluation purposes, a benchmark study is utilized. The proposed model achieves an accuracy of 93.7% while deciding the sentiment of a particular review. On the other hand, the department classification model achieves an accuracy of 93%. Furthermore, a user-friendly Python application is developed to make the models more accessible and easy to use.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1109/ubmk63289.2024.10773394
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
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article

AI Assisted Customer Review Sentiment Analysis and Department Classification Tool

Tacha Şerif, Burcu Selçuk, Berat Ilgaz Dursun
Sentiment Analysis and Opinion Mining
article

AI Assisted Customer Review Sentiment Analysis and Department Classification Tool

Tacha Şerif, Burcu Selçuk, Berat Ilgaz Dursun
article en

Abstract

Sentiment analysis is a crucial technique in electronic commerce as it enables businesses to understand customer opinions and emotions about products or services. By analyzing customer reviews, a company can enhance a product or service, improve customer satisfaction, adjust marketing strategies, and even increase sales by addressing negative comments. Accordingly, this study proposes an artificial i ntelligence integrated Python application to perform sentiment analysis on customer reviews to determine whether the review is positive, neutral, or negative. Moreover, a department classification m odel is also proposed to match each customer review to its potential department, such as logistics, sales, etcetera. For evaluation purposes, a benchmark study is utilized. The proposed model achieves an accuracy of 93.7% while deciding the sentiment of a particular review. On the other hand, the department classification model achieves an accuracy of 93%. Furthermore, a user-friendly Python application is developed to make the models more accessible and easy to use.

Yeditepe University (TR)
Openalex Percentile: Top 79%
Sentiment Analysis and Opinion Mining
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