JOURNAL ARTICLE

Sentiment analysis data by ShopeePayLater Twitter’s opinion using naïve Bayes classifier

Fauzillah IndrianiWahyu Catur Wibowo

Year: 2022 Journal:   AIP conference proceedings Vol: 2668 Pages: 070018-070018   Publisher: American Institute of Physics

Abstract

The Covid-19 pandemic effect on online shopping transactions rather than offline in order to prevent the spread of the Covid-19 virus. The paylater service help Indonesian become more easier to shop by taking out a loan. Shopee is one of the marketplaces that has a paylater service, namely Shopee PayLater, which is one of the payment methods on the Shopee platform that allows Shopee users to shop and only pay at a later date when it is due. Every new ShopeePayLater user want to know how the previous user responded as a form of testimony after using this feature via Twitter in the form of tweets. So it is necessary to conduct a sentiment analysis to find out public opinion with the existence of ShopeepayLater using the Naïve Bayes Classifier method so that it can provide useful information for Shopee and the public regarding ShopeePayLater services. Calculation of classification accuracy is carried out using G-Mean and AUC, because the sentiment of the tweets data is included in the imbalancedata category resulting in a G-Mean value of 64,79% and AUC of 66,12%.

Keywords:
Naive Bayes classifier Sentiment analysis Computer science Classifier (UML) Payment Artificial intelligence Information retrieval World Wide Web Support vector machine

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Topics

Multimedia Learning Systems
Physical Sciences →  Computer Science →  Information Systems
Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems
Information Retrieval and Data Mining
Physical Sciences →  Computer Science →  Information Systems
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