Nur Ain, Nor Azizan and Suhaila, Saee and Muhammad Abdullah, Yusof (2023) Discovering Popular Topics of Sarawak Gazette (SaGa) from Twitter Using Deep Learning. In: Soft Computing in Data Science : 7th International Conference, SCDS 2023 Virtual Event, January 24–25, 2023 Proceedings. Communications in Computer and Information Science (1771). Springer Nature Singapore Pte Ltd, pp. 178-192. ISBN 978-981-99-0405-1
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Abstract
The emergence of social media as an information-sharing platform is progressively increasing. With the progress of artificial intelligence, it is now feasible to analyze historical document from social media. This study aims to understand more about how people use their social media to share the content of the Sarawak Gazette (SaGa), one of the valuable historical documents of Sarawak. In the study, a short text of Tweet corpus relating to SaGa was built (according to some keyword search criteria). The Tweet corpus will then be analyzed to extract the topic based on a topic modeling, specifically, Latent Dirichlet Allocation (LDA). Then, the topics will be further classified with Convolutional Neural Network (CNN) classifier.
| Item Type: | Book Chapter |
|---|---|
| Uncontrolled Keywords: | Topic modeling · Twitter analysis · Sarawak Gazette. |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology |
| Depositing User: | Saee |
| Date Deposited: | 22 Mar 2023 06:54 |
| Last Modified: | 29 Aug 2023 00:47 |
| URI: | http://ir.unimas.my/id/eprint/41562 |
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