Sentiment Analysis Using Maximum Entropy on Application Reviews (Study Case: Shopee on Google Play)

Ulinnuha Rhohmawati, Isnandar Slamet, Hasih Pratiwi

Abstract


Shopee was one of the e-commerce application that could found on Google Play. The amount of Shopee application reviews on Google Play continues to grow over time. These make the company trying to get the overall information from all reviews because it would take a long time to read each of the reviews on Google Play. Therefore analysis was used using text mining. One part of text mining was sentiment analysis that applied the maximum entropy method to classification. Based on the results of the analysis found an accuracy of 97.32%. By using the maximum entropy method it could be concluded that word association obtained related to “application”, “promo”, “satisfy”, and “discount” for positive sentiment. Meanwhile for negative sentiment, the reviewers of Shopee application on Google Play were related to “problematic”, “login”, “old”, “verification”, and “expensive”. The results of this research in Indonesian.

Keywords


Shopee; Google Play; Sentiment Analysis; Maximum Entropy; Word Association

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References


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