Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Aug 9;23(8):e28249.
doi: 10.2196/28249.

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

Andi Muhammad Tri Sakti  1   2 , Emma Mohamad  1   2 , Arina Anis Azlan  1   2
Affiliations

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

Andi Muhammad Tri Sakti et al. J Med Internet Res. .

Abstract

Background: One of the successful measures to curb COVID-19 spread in large populations is 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 with those 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 toward movement restriction orders due to various claims such as human rights violations as well as sociocultural and economic issues. In Indonesia, society's adherence to its large-scale social restrictions (LSSRs) 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 increased number of daily confirmed cases and the total number of deaths, which was more than 6.21% (1351/21,745) of total active cases as of May 2020.

Objective: The aim of this study was 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 a sentiment analysis method with a supervised machine learning approach on COVID-19-related posts on selected media platforms (Twitter, Facebook, Instagram, and YouTube). The analysis was also performed 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 and May 31, 2020, were analyzed. 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 51.84% (n=1,002,947) of the total data (N=1,934,596) collected via the search engine. Negative sentiment was recorded at 35.51% (686,892/1,934,596) and neutral sentiment at 12.65% (244,757/1,934,596). The analysis of Twitter posts also showed that the majority of public have the emotion of "trust" toward the LSSR.

Conclusions: Public sentiment toward the LSSR appeared to be 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 toward the government's ability to manage this current global health crisis and win against COVID-19.

Keywords: COVID-19; Twitter; infodemiology; infoveillance; large-scale social restrictions; public sentiment; social media.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Machine learning workflow.
Figure 2
Figure 2
Data distribution for each platform.
Figure 3
Figure 3
Topic mapping of online news platforms.
Figure 4
Figure 4
Most retweeted tweets.
Figure 5
Figure 5
Total mentions by sentiment.
Figure 6
Figure 6
Sentiment trends in all media types.
Figure 7
Figure 7
Sentiment trends on May 17, 2020.
Figure 8
Figure 8
Emotion analysis.
Figure 9
Figure 9
Trend of public emotions.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Askitas N, Tatsiramos K, Verheyden B. Estimating worldwide effects of non-pharmaceutical interventions on COVID-19 incidence and population mobility patterns using a multiple-event study. Sci Rep. 2021 Jan 21;11(1):1972. doi: 10.1038/s41598-021-81442-x. doi: 10.1038/s41598-021-81442-x. - DOI - DOI - PMC - PubMed
    1. Mehta RM, Mehta R, Balaji AL, Mehta H. Perceptions on COVID19: A ground-level analysis to guide public policy. Lung India. 2020;37(3):282–283. doi: 10.4103/lungindia.lungindia_190_20. http://www.lungindia.com/article.asp?issn=0970-2113;year=2020;volume=37;... - DOI - PMC - PubMed
    1. Punn N, Sonbhadra S, Agarwal S. Monitoring Covid-19 Social Distancing with Person Detection and Tracking via Fine-tuned YOLO v3 and Deepsort Techniques. arXiv. 2021 http://export.arxiv.org/pdf/2005.01385
    1. Jarvis CI, Van Zandvoort K, Gimma A, Prem K, CMMID COVID-19 working group. Klepac P, Rubin GJ, Edmunds WJ. Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK. BMC Med. 2020 May 07;18(1):124. doi: 10.1186/s12916-020-01597-8. https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-020-01597-8 - DOI - DOI - PMC - PubMed
    1. Vogel L. How long will social distancing take to work? Experts weigh in on Canada's COVID-19 response. CMAJ. 2020 Apr 06;192(14):E382–E383. doi: 10.1503/cmaj.1095857. http://www.cmaj.ca/cgi/pmidlookup?view=long&pmid=32392531 - DOI - PMC - PubMed