Sentiment Analysis on Social Distancing and Physical Distancing on Twitter Social Media using Recurrent Neural Network (RNN) Algorithm

Authors

  • Fikri Aldi Nugraha Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia, Indonesia
  • Nisa Hanum Harani Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia, Indonesia http://orcid.org/0000-0003-2218-4165
  • Roni Habibi Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia, Indonesia
  • Rd. Nuraini Siti Fatonah Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia, Indonesia

DOI:

https://doi.org/10.15575/join.v5i2.632

Keywords:

Social Distancing, Sentiment Analysis, RNN Algorithm

Abstract

The government is seeking preventive steps to reduce the risk of the spread of Covid-19, one of which is social restrictions that have become popular with social distancing and physical distancing. One way to assess whether the steps taken by the government regarding social and physical distancing are accepted or not by the community is by conducting sentiment analysis. The process of sentiment analysis is carried out using a variant of the Recurrent Neural Network (RNN), namely Long Short-Term Memory (LSTM). In this study, the results obtained from the sentiment analysis, where the public response to social distancing and physical distancing has more positive sentiments than negative sentiments. To measure the accuracy level of sentiment analysis using the Recurrent Neural Network (RNN) algorithm and evaluation of the modeling is done using confusion matrix where the results obtained for the training dataset are 89% accuracy, 89% recall, 89% precision, and 89% F1 Score. Meanwhile, for the test dataset, an accuracy of 80% was obtained, a recall of 79%, a precision of 81%, and an F1 score of 80%.

Author Biographies

Fikri Aldi Nugraha, Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia

D4 Teknik Informatika

Nisa Hanum Harani, Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia

D4 Teknik Informatika

Roni Habibi, Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia

D4 Teknik Informatika

Rd. Nuraini Siti Fatonah, Department of Informatics, Politeknik Pos Indonesia, Bandung, Indonesia

D4 Teknik Informatika

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Published

2020-12-03

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