Discovering Popular Topics of Sarawak Gazette (SaGa) from Twitter Using Deep Learning - Nur Ain, Nor Azizan; Suhaila, Saee; Muhammad Abdullah, Yusof (Springer Nature Singapore Pte Ltd, 2023)
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 With the progress of artificial intelligence, it is now feasible to analyze historical document from social media.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more about how people use their social media to share the content of the Sarawak Gazette (SaGa), one of the valuable historical documents of Sarawak.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.