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Journal : International Journal of Information Engineering and Science

Using Natural Language Processing to Enhance Customer Sentiment Analysis in Ecommerce Andi Prasetyo; Rina Dwi Lestari; Rudi Hartono
International Journal of Information Engineering and Science Vol. 1 No. 2 (2024): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v1i2.90

Abstract

Customer sentiment analysis provides valuable insights for ecommerce businesses, but traditional methods often fall short in handling complex and contextrich language. This paper explores the use of Natural Language Processing (NLP) techniques, including BERT and transformer models, to improve sentiment analysis accuracy in ecommerce. The study compares the performance of different NLP models in capturing nuanced customer sentiment from online reviews. Findings indicate that advanced NLP techniques substantially increase accuracy and offer practical applications for improving customer experience and business strategy in ecommerce.Keywords: Natural Language Processing, sentiment analysis, ecommerce, customer experience, BERT, transformer models.