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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Feb 26, 2021
Date Accepted: Jun 15, 2021
Date Submitted to PubMed: Aug 12, 2021

The final, peer-reviewed published version of this preprint can be found here:

Mining of Opinions on COVID-19 Large-Scale Social Restrictions in Indonesia: Public Sentiment and Emotion Analysis on Online Media

Tri Sakti AM, Mohamad E, Azlan AA

Mining of Opinions on COVID-19 Large-Scale Social Restrictions in Indonesia: Public Sentiment and Emotion Analysis on Online Media

J Med Internet Res 2021;23(8):e28249

DOI: 10.2196/28249

PMID: 34280116

PMCID: 8360340

MINING OF OPINIONS ON COVID-19 LARGE-SCALE SOCIAL RESTRICTIONS IN INDONESIA: PUBLIC SENTIMENT AND EMOTION ANALYSIS ON ONLINE MEDIA

  • Andi Muhammad Tri Sakti; 
  • Emma Mohamad; 
  • Arina Anis Azlan

ABSTRACT

Background:

Among successful measures to curb COVID-19 spread in large populations includes the implementation of a movement restriction order. Globally, it was observed that countries implementing strict movement control were more successful in controlling the spread of the virus as compared to countries with less stringent measures. Society’s adherence to the movement control order has helped expedite the process to flatten the pandemic curve as seen in countries such as China and Malaysia. At the same time, there are countries facing challenges with society’s nonconformity towards movement restriction orders due to various claims such as human rights violations as well as socio-cultural and economic issues. In Indonesia, society’s adherence to its Large-Scale Social Restrictions (LSSR) order is also a challenge to achieve. Indonesia is regarded as among the worst in Southeast Asian countries in terms of managing the spread of COVID-19. It is proven by the significant number of daily confirmed cases and the total number of deaths which was more than 6% of total active cases as of May 2020.

Objective:

To explore public sentiments and emotions toward the LSSR and identify issues, fear and reluctance to observe this restriction among the Indonesian public.

Methods:

This study adopts sentiment analysis method with supervised machine learning approach on COVID-19 related posts on selected media platforms, which are Twitter, Facebook, Instagram, and Youtube. The analysis was also done on COVID-19 related news contained in more than 500 online news platforms recognized by the Indonesian Press Council. Social media posts and news originating from Indonesian online media between March 31 to May 31, 2020 were analyzed. Additionally, emotion analysis on Twitter platform was also performed to identify collective public emotions toward the LSSR.

Results:

The study found that positive sentiment surpasses other sentiment categories by 1,002,947 mentions (52%) of the total data collected via the search engine. Negative sentiment was recorded at 36%, and neutral sentiment at 13%. The analysis of Twitter posts also showed that the majority of public have the emotion of “trust” toward the LSSR.

Conclusions:

Overall public sentiment toward the LSSR was positive despite doubts on government consistency in executing the LSSR. The emotion analysis also concluded that the majority of people believe in LSSR as the best method to break the chain of COVID-19 transmission. Overall, Indonesians showed trust and expressed hope towards the government’s ability to manage this current global health crisis and win against COVID-19.


 Citation

Please cite as:

Tri Sakti AM, Mohamad E, Azlan AA

Mining of Opinions on COVID-19 Large-Scale Social Restrictions in Indonesia: Public Sentiment and Emotion Analysis on Online Media

J Med Internet Res 2021;23(8):e28249

DOI: 10.2196/28249

PMID: 34280116

PMCID: 8360340

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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