Emotion Classification of Indonesian Tweets using BERT Embedding
Twitter is one of the social media that has the largest users in the world. Indonesia is one of the countries that has the 5th largest number of Twitter users in the world which causes a high possibility of conflict between Indonesian Twitter users due to emotional tension in tweets. In this paper,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Politeknik Negeri Batam
2023-11-01
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| Series: | Journal of Applied Informatics and Computing |
| Subjects: | |
| Online Access: | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/6528 |
| _version_ | 1827589956400316416 |
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| author | Muhammad Habib Algifari Eko Dwi Nugroho |
| author_facet | Muhammad Habib Algifari Eko Dwi Nugroho |
| author_sort | Muhammad Habib Algifari |
| collection | DOAJ |
| description | Twitter is one of the social media that has the largest users in the world. Indonesia is one of the countries that has the 5th largest number of Twitter users in the world which causes a high possibility of conflict between Indonesian Twitter users due to emotional tension in tweets. In this paper, we will compare the BERT embedding method with CNN and LSTM. The results of this experiment are BERT-CNN has the best performance results which has an accuracy of 61% compared to BERT-LSTM. In the experiment several stages of data preprocessing, data cleaning, data spiting and data training were carried out and the results were evaluated using confusion metrics. |
| first_indexed | 2024-03-09T01:08:54Z |
| format | Article |
| id | doaj.art-b99df7e37a8941a1946a437d35592890 |
| institution | Directory Open Access Journal |
| issn | 2548-6861 |
| language | English |
| last_indexed | 2024-03-09T01:08:54Z |
| publishDate | 2023-11-01 |
| publisher | Politeknik Negeri Batam |
| record_format | Article |
| series | Journal of Applied Informatics and Computing |
| spelling | doaj.art-b99df7e37a8941a1946a437d355928902023-12-11T08:06:22ZengPoliteknik Negeri BatamJournal of Applied Informatics and Computing2548-68612023-11-017217217610.30871/jaic.v7i2.65286528Emotion Classification of Indonesian Tweets using BERT EmbeddingMuhammad Habib Algifari0Eko Dwi Nugroho1Institut Teknologi SumateraInstitut Teknologi SumateraTwitter is one of the social media that has the largest users in the world. Indonesia is one of the countries that has the 5th largest number of Twitter users in the world which causes a high possibility of conflict between Indonesian Twitter users due to emotional tension in tweets. In this paper, we will compare the BERT embedding method with CNN and LSTM. The results of this experiment are BERT-CNN has the best performance results which has an accuracy of 61% compared to BERT-LSTM. In the experiment several stages of data preprocessing, data cleaning, data spiting and data training were carried out and the results were evaluated using confusion metrics.https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/6528bertcnnlstmtwitter |
| spellingShingle | Muhammad Habib Algifari Eko Dwi Nugroho Emotion Classification of Indonesian Tweets using BERT Embedding Journal of Applied Informatics and Computing bert cnn lstm |
| title | Emotion Classification of Indonesian Tweets using BERT Embedding |
| title_full | Emotion Classification of Indonesian Tweets using BERT Embedding |
| title_fullStr | Emotion Classification of Indonesian Tweets using BERT Embedding |
| title_full_unstemmed | Emotion Classification of Indonesian Tweets using BERT Embedding |
| title_short | Emotion Classification of Indonesian Tweets using BERT Embedding |
| title_sort | emotion classification of indonesian tweets using bert embedding |
| topic | bert cnn lstm |
| url | https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/6528 |
| work_keys_str_mv | AT muhammadhabibalgifari emotionclassificationofindonesiantweetsusingbertembedding AT ekodwinugroho emotionclassificationofindonesiantweetsusingbertembedding |