Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Vol. 6 No. 1 (2026): October 2026

Sentiment Analysis of Duolingo Application Reviews on Google Play Using the Support Vector Machine Method

Nur Jihan Arifi (STMIK Kaputama)
Novriyenni (STMIK Kaputama)
Muammar Khadapi (STMIK Kaputama)



Article Info

Publish Date
15 Oct 2026

Abstract

Abstract The Duolingo app is one of the most widely used language-learning apps available on Google Play. The large number of reviews posted by users makes sentiment analysis necessary to identify trends in user opinions regarding the app—whether positive, negative, or neutral. This study aims to analyze the sentiment of Duolingo app user reviews on Google Play using the Support Vector Machine (SVM) algorithm. Research data was obtained through web scraping of 1,220 user reviews, followed by preprocessing, sentiment labeling, and word weighting using TF-IDF prior to the classification process using the SVM algorithm. The results show that positive sentiment accounted for 57.1%, negative sentiment for 30.3%, and neutral sentiment for 12.6%. Based on the test results, the Support Vector Machine (SVM) algorithm achieved an accuracy of 79.23%, demonstrating fairly good performance in classifying the sentiment of user reviews for the Duolingo app on Google Play. Keywords: Sentiment Analysis, Duolingo, Google Play, Support Vector Machine (SVM).

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Journal Info

Abbrev

JAIEA

Publisher

Subject

Automotive Engineering Computer Science & IT Control & Systems Engineering

Description

The Journal of Artificial Intelligence and Engineering Applications (JAIEA) is a peer-reviewed journal. The JAIEA welcomes papers on broad aspects of Artificial Intelligence and Engineering which is an always hot topic to study, but not limited to, cognition and AI applications, engineering ...