ArticleComputer methods and programs in biomedicine2021
Social Media Data Analytics for Outbreak Risk Communication: Public Attention on the "New Normal" During the COVID-19 Pandemic in Indonesia.
Article in Computer methods and programs in biomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A bimodal longitudinal investigation on changes in sentiments over social media interactions owing to COVID-19 pandemic.Scientific reports · 2025Article
- Disaster risk reduction communication during the Mount Semeru eruption in East Java, Indonesia.Jamba (Potchefstroom, South Africa) · 2025Article
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- The role of risk perception, risk communication, and demographic factors in COVID-19 preventive behaviors: an online survey in Iran.Osong public health and research perspectives · 2022Article
- Social media sentiment analysis to monitor the performance of vaccination coverage during the early phase of the national COVID-19 vaccine rollout.Computer methods and programs in biomedicine · 2022Article
- Public Perception Before and After COVID-19 Vaccine Pass for the Unvaccinated to Eat Alone: Social Media Data Analytics.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
backgroundAfter 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.
objectiveThis 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".
methodFrom 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.
resultWe 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.
conclusionOur 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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