Social Media Data Analytics for Outbreak Risk Communication: Public Attention on the "New Normal" During the COVID-19 Pandemic in Indonesia. (June 2021) - Rahmanti, Annisa Ristya; Ningrum, Dina Nur Anggraini; Lazuardi, Lutfan; Yang, Hsuan-Chia; Li, Yu-Chuan(Jack)
Highlights: Twitter is a powerful tool to disseminate government actions in handling an emergency response. Learning public attention is very crucial for appropriate crisis management during a pandemic. The majority of Indonesian Twitter users express a "positive" sentiment towards the "New Normal". The trend of public attention was affected by a strong government outbreak risk communication. The social network analysis shows a "positive" statement dominated by the government account. 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.