 Sentiment analysis on customer reviews in Indonesian marketplace using natural language processing (a case study of organic face mask)Nur Izzaty, Adelia Shinta, Riski Arifin and Sri Rahmawati International Journal of Data Mining, Modelling and Management, 2025, vol. 17, issue 3, 364-381 Abstract: The increasing development of technology nowadays has led to the transformation of customers behaviour in purchasing products, from offline to online through marketplace. One of the most popular marketplaces in Indonesia is Shopee with the best seller skincare product is organic face mask. This study aims to analyse the sentiment of customer reviews using natural language processing (NLP) and term frequency-inversed document frequency (TF-IDF). The result revealed that from 882 reviews extracted, 89.7% was classified as positive reviews (rating 4 and 5) and the rest as much as 10.3% was the negative ones (rating 1 and 2). The sentiments were visualised using word cloud. Among the positive reviews were 'very good', 'quickly absorbed', and 'convenient'. Meanwhile, among the negative reviews were 'disappointed', 'delivery', and 'acne'. In summary, the performance metrics used for the evaluation of the classification model showed that the model accuracy reached 95%. Keywords: customer reviews; natural language processing; NLP; sentiment analysis; term frequency-inverse document frequency; TF-IDF; skincare; organic face mask. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdmmm:v:17:y:2025:i:3:p:364-381 Access Statistics for this article More articles in International Journal of Data Mining, Modelling and Management from Inderscience Enterprises Ltd |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.