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

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.

Sentiment Analysis Based on Review of Puncak B29 Lumajang using Backpropagation Neural Network

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“…From the tourism sector, developments in internet-based technology can be used to dig up information about tourism spots and process existing data to measure quality through comparing visitors' opinions about a tourism spot [2]. The results of these quality measurements can be used as a consideration for users to determine decisions in choosing tourist attractions [3], and can be useful for tourism managers as evaluation material to improve the quality of these tourist attractions so that they can attract more visitors [4].…”

Sentiment Analysis Of Development Jakarta-Bandung High-Speed Train Using Twitter Social Media With BNN Method

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