Andi Muhammad Tri SaktI, and Emma Mohamad, and Andi Eliyah Humairah, and Arina Anis Azlan, (2024) Indonesian public response to school reopening during pandemic: capturing sentiment and emotion using X data. Jurnal Komunikasi ; Malaysian Journal of Communication, 40 (2). pp. 111-129. ISSN 0128-1496
![]() |
PDF
413kB |
Official URL: https://ejournal.ukm.my/mjc/issue/view/1710
Abstract
The COVID-19 pandemic caused global disruption for education delivery. To prevent adverse effects on student education, authorities instructed education institutions to implement virtual learning. For a developing country like Indonesia, inadequate knowledge and skills in utilizing e-learning applications, unstable networks, and a lack of virtual learning facilities were the biggest concerns in conducting virtual learning. This led school reopening to be a topic hotly discussed on public platforms when the plan was first introduced by the Indonesian government at the end of 2021. Uncertainty surrounding the implementation of school reopening, concerns about the risk of being infected by COVID-19, and concerns about the effects of learning loss on students increased the opinion polarization among the Indonesian public at the time. This study examines public opinion on school reopening during the pandemic and identifies Indonesian public sentiment and emotions toward the issue. A supervised machine learning approach was utilized to mine X (formerly known as Twitter) data that reflected the public opinion toward implementing face-to-face learning during the COVID-19 pandemic in Indonesia. Sentiment analysis on X for six months (September 2021–January 2022) revealed that the negative opinions (n=23,830) were prominent, far more than the positive (n=14,507) and neutral (n=5,413) opinions. Emotion analysis revealed that most of the public felt joy about school reopening. This study highlights some learnings from the pandemic for future crisis preparedness. Through sentiment analysis, mixed reactions toward school reopening were observed. This provides an understanding of public emotions that governments should listen to and act on to build trust.
Item Type: | Article |
---|---|
Keywords: | COVID-19; School reopening; Sentiment analysis; Emotion analysis; Machine learning |
Journal: | Jurnal Komunikasi ; Malaysian Journal of Communication |
ID Code: | 23945 |
Deposited By: | Mohd Hamka Md. Nasir |
Deposited On: | 07 Aug 2024 06:39 |
Last Modified: | 12 Aug 2024 02:39 |
Repository Staff Only: item control page