International Journal of Information Science and Management (IJISM)

Analysis of Emotional Aspect of Twitter Postings about Large Scale Social Limitations in Suppressing the Spread of COVID-19

Document Type : Articles

Authors

Adhi Paramartha
Paulus Mudjihartono
Andi Wahyu Rahardjo Emanuel

Atma Jaya Yogyakarta University

Abstract
The spread of COVID-19 has recently become a public concern. There are many public emotions regarding implementing the Large-Scale Social Restrictions (PSBB), which was especially implemented in Jakarta, first implemented in Indonesia. People have various emotions mirroring their tweets in making statements on social media, especially Twitter. Emotional expressions can be joy, sadness, anger, and fear. This study aims to determine the impact of the implementation of PSBB in reducing the spread of COVID-19 on people's emotional factors on Twitter. The method used in this research is the SentiStrength method and Support Vector Machine. Furthermore, the comparison between the two methods is completed to determine which one is better. The tweet data used were 12,735 lines from 10 April 2020 to 21 August 2020. The highest accuracy achieved of SentiStrength and SVM is 88.33% and 73.33%, respectively. Similarly, f-measure of SentiStrength (88.14%) outperforms SVM (75%). This research shows that the implementation of PSBB on public emotional factors on Twitter is that happy emotions with the highest sentiment are positive sentiments, reaching 5246 sentiments.https://dorl.net/dor/20.1001.1.20088302.2022.20.2.1.6

Keywords

Large-Scale Social Restrictions
emotional factors
COVID-19
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  • Receive Date 08 December 2020
  • Accept Date 03 December 2022

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