Analysis of Twitter Users Sentiment against the Covid-19 Outbreak Using the Backpropagation Method with Adam Optimization

  • Theresia Hendrawati STMIK STIKOM Indonesia
  • Christina Purnama Yanti

Abstract

This research tries to take advantage of Twitter by analyzing Indonesian-language tweets that discuss the Covid-19 virus outbreak to find out what Twitter users think about the Covid-19 virus outbreak. This study tries to analyze sentiment to see opinions on Covid-19 tweets that contains Posittive, Negative or Neutral sentiments using Multi-layer Perceptron (MLP) using Backprogragation with Adam optimization. We collected 200 documents (tweets) in Indonesian about Covid-19 that were tweeted since November 2019 and then trained them to get our MLP Backpropagation model. Our model managed to get an accuracy of up to 70% with f1-scores for positive, negative, and neutral classes respectively 0.77, 0.75, and 0.5 from a maximum value of 1. This shows that our model is quite successful in carrying out the sentiment classification process for Indonesian tweets with the Covid-19 theme.

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References

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Published
2021-02-27
How to Cite
HENDRAWATI, Theresia; YANTI, Christina Purnama. Analysis of Twitter Users Sentiment against the Covid-19 Outbreak Using the Backpropagation Method with Adam Optimization. Journal of Electrical, Electronics and Informatics, [S.l.], v. 5, n. 1, p. 1-4, feb. 2021. ISSN 2622-0393. Available at: <https://ojs.unud.ac.id/index.php/JEEI/article/view/65626>. Date accessed: 27 sep. 2021. doi: https://doi.org/10.24843/JEEI.2021.v05.i01.p01.