文章基本信息

标题：Sentiment Analysis of COVID-19 using Multimodal Fusion Neural Networks
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作者：Ermatita Ermatita ; Abdiansah Abdiansah ; Dian Palupi Rini 等
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.