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Sentiment Analysis Covid-19 Spread Tracing on Google Play Store Application

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 436)

Abstract

Sentiment analysis of users of tracing the spread of Covid-19 using Google Playstore application review in Southeast Asia, especially the “Peduli Lindungi” application in Indonesia, the “Trace Together” application in Singapore, “My Sejahtera” in Malaysia. The dataset used is a total of 6000 reviews from each application of 2000 reviews during the period June to December 2021. Sentiment analysis classification uses random forest algorithm and logistic regression resulted negative sentiment dominant. Sentiment positive vs negative for the “Peduli Lindungi” was 29% vs 71%, the “Trace Together” was 25% vs 75%, and “My Sejahtera” was 32% vs 68%. Classification performance checked by confusion matrix, logistic regression and random forest resulted in almost the same accuracy, but logistic regression was better with details of accuracy 87%, 84%, and 85%, precision 89%, 85%, 85%, F1 score and recall 86%, 84%, 85% respectively for the “Peduli Lindungi”, the “Trace Together”, and “My Sejahtera” applications, respectively.

Keywords

  • Sentiment analysis
  • Covid-19
  • Google play store

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Acknowledgements

The author thanks all parties that provide support for this research study. Special thanks to linguist Mr. David Sutjipto for his help in labeling review of the tracing Covid-19 application in google playstore and department of Information Technology, Universitas Amikom, Yogyakarta.

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Correspondence to Usman Wijaya .

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Wijaya, U., Yulianto, Y., Anggraeni, M.D., Prabowo, S.B.J.A., Izul Ula, M., Utami, E. (2022). Sentiment Analysis Covid-19 Spread Tracing on Google Play Store Application. In: Seyman, M.N. (eds) Electrical and Computer Engineering. ICECENG 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 436. Springer, Cham. https://doi.org/10.1007/978-3-031-01984-5_8

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  • DOI: https://doi.org/10.1007/978-3-031-01984-5_8

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-01984-5

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