| Issue |
E3S Web Conf.
Volume 448, 2023
The 8th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2023)
|
|
|---|---|---|
| Article Number | 02032 | |
| Number of page(s) | 9 | |
| Section | Information System | |
| DOI | https://doi.org/10.1051/e3sconf/202344802032 | |
| Published online | 17 November 2023 | |
Sentiment Analysis On Movie Streaming Services On Twitter Using LDA and SVM Methods
1 Magister of Information System, School of Postgraduate, Diponegoro Univeristy, Semarang, Indonesia
2 Department of Physis, Diponegoro Univeristy, Semarang, Indonesia
3 Department of Mathematics, Diponegoro Univeristy, Semarang, Indonesia
* Corresponding author: hanidaroy@gmail.com
Many online platforms for movie streaming have emerged nowadays in Indonesia with the development of technology. Streaming platforms that are widely used by the public are Netflix, Disney+, HBO Go, WeTV, Vidio. A lot of comparisons between streaming platforms have become a topic of discussion on social media. The opinions expressed by users of the streaming platform greatly affect other users who want to watch the movie. The transmission of opinions from users becomes positive and negative comments that are received by the public and spread widely on social media. Opinions that contain both positive and negative comments become a problem and can affect other users who want to watch movies through streaming platforms. The opinions of users about the streaming platform can be analyzed through sentiment analysis. At the stage of data collection using scrapy framework tools with Python, as much as 1,500 lines of text are preprocessed. LDA method to present topics that contain representative words. Classification using the Support Vector Machine (SVM) gets more positive comments than negative comments. The test results obtained an accuracy of 0.82, recall of 0.8, F1 score of 0.79, and precision of 0.8.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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