Sentiment Analysis of Indonesian Government Policies In Handling Covid 19 Through Twitter Data

被引：0

作者：

Sujiwo, Bagus ^{[1
]}

Wibowo, Antoni ^{[1
]}

Saputro, Dewi Retno Sari ^{[1
,2
]}

机构：

[1] Bina Nusantara Univ, BINUS Grad Program, Comp Sci Dept, Comp Sci, Jakarta 11480, Indonesia

[2] Univ Sebelas Maret, Program Studi Matemat FMIPA UNS, Surakarta 57126, Indonesia

来源：

2021 4TH INTERNATIONAL SEMINAR ON RESEARCH OF INFORMATION TECHNOLOGY AND INTELLIGENT SYSTEMS (ISRITI 2021) | 2020年

关键词：

Covid; 19; Policy; Naive Bayes; SVM; LSTM;

D O I：

10.1109/ISRITI54043.2021.9702784

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presented a sentiment analysis of the Indonesian government's policies in overcoming Covid 19 through twitter data using several classification methods, namely SVM , Naive Bayes, and LSTM. Based on the analysis of the twitter data, it was found that the twitter community in Indonesia gave negative sentiments to government policies in handling Covid 19. From the experimental results, it was found that SVM gave the best sentiment results compared to Naive Bayes and LSTM by providing an accuracy of 88.5%.

引用

页数：5

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