Sentiment Analysis of YouTube Users on Blackpink Kpop Group Using IndoBERT
| Title: | Sentiment Analysis of YouTube Users on Blackpink Kpop Group Using IndoBERT |
|---|---|
| Authors: | Slamet Riyadi, Lathifah Khansa Salsabila, Cahya Damarjati, Rohana Abdul Karim |
| Source: | Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi, Vol 8, Iss 2 (2024) |
| Publisher Information: | Universitas Nusantara PGRI Kediri, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Information technology LCC:Electronic computers. Computer science |
| Subject Terms: | Sentiment Analysis, Blackpink, IndoBERT, Youtube, K-Pop, Information technology, T58.5-58.64, Electronic computers. Computer science, QA75.5-76.95 |
| More Details: | Background: The Korean Pop (K-Pop) phenomenon has become an important part of popular culture worldwide, with Blackpink being one of the most influential groups. Analyzing sentiment toward Blackpink is urgent, given its growing popularity and wide influence among fans worldwide. In the present technological era, social media platforms such as YouTube have evolved into a space where artists and their fans may interact with each other. As a consequence, social media has become a powerful tool for assessing the emotional tone and sentiment conveyed by individuals. Objective: This research aims to explore the trend of public sentiment towards Blackpink and evaluate how well the IndoBERT model analyzes the sentiment of Indonesian texts. Methods: The objective of this study is to examine the pattern of public sentiment towards Blackpink and assess the proficiency of the IndoBERT model in analyzing the sentiment of Indonesian writings. Results: The findings demonstrated that the IndoBERT model had an exceptional level of precision, achieving a 98% accuracy rate. In addition, it obtained a f1, recall, and accuracy score of 95%. The remarkable results demonstrate the efficacy of the IndosBERT technique in evaluating the emotion of Indonesian-language literature towards Blackpink. Conclusion: This study enhances the knowledge of how fans and audiences react to K-pop material and establishes a foundation for future research and advancement. The impressive precision of the IndoBERT model showcases its capacity for sentiment analysis in Indonesian literature, making it a useful tool for future research endeavors. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English Indonesian |
| ISSN: | 2580-409X 2549-6824 |
| Relation: | https://ojs.unpkediri.ac.id/index.php/intensif/article/view/22678; https://doaj.org/toc/2580-409X; https://doaj.org/toc/2549-6824 |
| DOI: | 10.29407/intensif.v8i2.22678 |
| Access URL: | https://doaj.org/article/6d97a004cb074533b7191ce8b91b2b92 |
| Accession Number: | edsdoj.6d97a004cb074533b7191ce8b91b2b92 |
| Database: | Directory of Open Access Journals |
| ISSN: | 2580409X 25496824 |
|---|---|
| DOI: | 10.29407/intensif.v8i2.22678 |
| Published in: | Intensif: Jurnal Ilmiah Penelitian Teknologi dan Penerapan Sistem Informasi |
| Language: | English Indonesian |