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, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
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), Indonesia.
Comput Methods Programs Biomed. 2021 Jun;205:106083. doi: 10.1016/j.cmpb.2021.106083. Epub 2021 Apr 6.
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.
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".
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.
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.
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.
在实施部分封锁两个月后，印度尼西亚政府宣布了“新常态”政策，以防止该国经济进一步崩溃。这项政策受到了许多批评，因为印度尼西亚仍在经历感染病例数量的波动。通过有效的风险沟通了解公众的看法，可以帮助政府向公众传达适当的信息，提高人们的遵从度，避免疾病进一步传播。
本研究观察了如何利用 Twitter 等社交媒体平台进行风险沟通，以衡量公众对 COVID-19 相关“新常态”问题的关注。
2020 年 5 月 21 日至 6 月 18 日，我们使用 Drone Emprit Academy（DEA）引擎，通过关键词“#NewNormal”和“新常态”，对所有与 COVID-19 相关的推文进行存档。DEA 搜索 API 收集了所有请求的推文，并对累积推文进行趋势分析、分词和词频分析。我们进一步使用情感分析来分析公众的看法，并通过情绪分析来识别主要推文。
我们从 137,057 名活跃用户那里收集了 284,216 条推文。从趋势分析中，我们观察到公众对“新常态”关注度的变化趋势分为三个阶段。情感分析的结果表明，超过一半（52%）的人对“新常态”问题持“积极”态度，而只有 41%的人持“消极”态度。我们的研究还表明，由于政府行动和疾病传播的影响，公众的情绪趋势已经从“消极”逐渐转变为“积极”。对情绪分析的更详细分析表明，大多数公众情绪（77.6%）依赖于“信任”、“期待”和“喜悦”的情绪。同时，人们也对印度尼西亚政府在病例数量波动的情况下推进“新常态”概念感到惊讶（8.62%）。
我们的研究结果为政府在应对 COVID-19 大流行期间提供了一个机会，使其能够在不确定时期利用 Twitter 进行快速决策和政策评估。
