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  • 标题:Sentiment Analysis of COVID-19 using Multimodal Fusion Neural Networks
  • 本地全文:下载
  • 作者:Ermatita Ermatita ; Abdiansah Abdiansah ; Dian Palupi Rini
  • 期刊名称:TEM Journal
  • 印刷版ISSN:2217-8309
  • 电子版ISSN:2217-8333
  • 出版年度:2022
  • 卷号:11
  • 期号:3
  • 页码:1316-1321
  • DOI:10.18421/TEM113-41
  • 语种:English
  • 出版社:UIKTEN
  • 摘要:The purpose of this study creates a Sentiment Analysis model of COVID-19 using Multimodal Fusion Neural Networks in real time to model and visualize COVID-19 in Indonesia. This study obtained 87 percent accuracy using the Multimodal Fusion Neural Networks model, a higher 5 percent than the benchmarking model Convolutional Neural Networks. This study proves that the sentiment model built is quite promising and relevant to be implemented.
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