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Social Media Data Analytics for Outbreak Risk Communication: Public Attention on the "New Normal" During the COVID-19 Pandemic in Indonesia.
Rahmanti, Annisa Ristya; Ningrum, Dina Nur Anggraini; Lazuardi, Lutfan; Yang, Hsuan-Chia; Li, Yu-Chuan Jack.
  • Rahmanti AR; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Department of Health Policy Management, Faculty of Medicine,
  • Ningrum DNA; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Public Health Department, Universitas Negeri Semarang (UNNES)
  • Lazuardi L; Department of Health Policy Management, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
  • Yang HC; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Public Health Department, Universitas Negeri Semarang (UNNES)
  • Li YJ; Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan; Research Center of Big Data and Meta-analysis, Wan Fang Hospi
Comput Methods Programs Biomed ; 205: 106083, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1261871
ABSTRACT

BACKGROUND:

After two months of implementing a partial lockdown, the Indonesian government had announced the "New Normal" policy to prevent a further economic crash in the country. This policy received many critics, as Indonesia still experiencing a fluctuated number of infected cases. Understanding public perception through effective risk communication can assist the government in relaying an appropriate message to improve people's compliance and to avoid further disease spread.

OBJECTIVE:

This study observed how risk communication using social media platforms like Twitter could be adopted to measure public attention on COVID-19 related issues "New Normal".

METHOD:

From May 21 to June 18, 2020, we archived all tweets related to COVID-19 containing keywords "#NewNormal", and "New Normal" using Drone Emprit Academy (DEA) engine. DEA search API collected all requested tweets and described the cumulative tweets for trend analysis, word segmentation, and word frequency. We further analyzed the public perception using sentiment analysis and identified the predominant tweets using emotion analysis.

RESULT:

We collected 284,216 tweets from 137,057 active users. From the trend analysis, we observed three stages of the changing trend of the public's attention on the "New Normal". Results from the sentiment analysis indicate that more than half of the population (52%) had a "positive" sentiment towards the "New Normal" issues while only 41% of them had a "negative" perception. Our study also demonstrated the public's sentiment trend has gradually shifted from "negative" to "positive" due to the influence of both the government actions and the spread of the disease. A more detailed analysis of the emotion analysis showed that the majority of the public emotions (77.6%) relied on the emotion of "trust", "anticipation", and "joy". Meanwhile, people were also surprised (8.62%) that the Indonesian government progressed to the "New Normal" concept despite a fluctuating number of cases.

CONCLUSION:

Our findings offer an opportunity for the government to use Twitter in the process of quick decision-making and policy evaluation during uncertain times in response to the COVID-19 pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Comput Methods Programs Biomed Journal subject: Medical Informatics Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Comput Methods Programs Biomed Journal subject: Medical Informatics Year: 2021 Document Type: Article