Jurnal INFOTEL
Vol 13 No 3 (2021): August 2021

Multi-aspect sentiment analysis on netflix application using latent dirichlet allocation and support vector machine methods

Attala Rafid Abelard (Telkom University)
Yuliant Sibaroni (Telkom University)



Article Info

Publish Date
31 Aug 2021

Abstract

Among many film streaming platforms that have sprung up, Netflix is ​​the platform that has the most subscribers compared to the other platforms. However, not all reviews provided by the Netflix users are good reviews. These reviews will later be analyzed to determine what aspects are reviewed by the users based on reviews written on the Google Play Store, using the Latent Dirichlet Allocation (LDA) method. Then, the classification process using the Support Vector Machine (SVM) method will be carried out to determine whether each of these reviews is included in the positive or negative class (Sentiment Analysis). There are 2 scenarios that were carried out in this study. The first scenario resulted that the best number of LDA topics to be used is 40, and the second scenario resulted that the use of filtering process in the preprocessing stage reduces the score of the f1-score. Thus, this study resulted in the best performance score on LDA and SVM testing with 40 topics, and without running the filtering process with the score of 78.15%.

Copyrights © 2021






Journal Info

Abbrev

infotel

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published ...