Zhou Jianlong, Yang Shuiqiao, Xiao Chun, Chen Fang
Data Science Institute, University of Technology Sydney, Sydney, Australia.
Faculty of Transdisciplinary Innovation, University of Technology Sydney, Sydney, Australia.
SN Comput Sci. 2021;2(3):201. doi: 10.1007/s42979-021-00596-7. Epub 2021 Apr 9.
The outbreak of the novel Coronavirus Disease 2019 (COVID-19) has caused unprecedented impacts to people's daily life around the world. Various measures and policies such as lockdown and social-distancing are implemented by governments to combat the disease during the pandemic period. These measures and policies as well as virus itself may cause different mental health issues to people such as depression, anxiety, sadness, etc. In this paper, we exploit the massive text data posted by Twitter users to analyse the sentiment dynamics of people living in the state of New South Wales (NSW) in Australia during the pandemic period. Different from the existing work that mostly focuses on the country-level and static sentiment analysis, we analyse the sentiment dynamics at the fine-grained local government areas (LGAs). Based on the analysis of around 94 million tweets that posted by around 183 thousand users located at different LGAs in NSW in 5 months, we found that people in NSW showed an overall positive sentimental polarity and the COVID-19 pandemic decreased the overall positive sentimental polarity during the pandemic period. The fine-grained analysis of sentiment in LGAs found that despite the dominant positive sentiment most of days during the study period, some LGAs experienced significant sentiment changes from positive to negative. This study also analysed the sentimental dynamics delivered by the hot topics in Twitter such as government policies (e.g. the Australia's JobKeeper program, lockdown, social-distancing) as well as the focused social events (e.g. the Ruby Princess Cruise). The results showed that the policies and events did affect people's overall sentiment, and they affected people's overall sentiment differently at different stages.
2019年新型冠状病毒病（COVID-19）的爆发给全球人们的日常生活带来了前所未有的影响。在疫情期间，各国政府实施了诸如封锁和社交距离等各种措施和政策来抗击疫情。这些措施、政策以及病毒本身可能会给人们带来不同的心理健康问题，如抑郁、焦虑、悲伤等。在本文中，我们利用推特用户发布的海量文本数据，分析了澳大利亚新南威尔士州（NSW）居民在疫情期间的情绪动态。与现有大多集中在国家层面和静态情绪分析的工作不同，我们在细粒度的地方政府区域（LGAs）层面分析情绪动态。基于对新南威尔士州不同地方政府区域约18.3万名用户在5个月内发布的约9400万条推文的分析，我们发现新南威尔士州居民总体呈现积极的情绪极性，且COVID-19疫情在疫情期间降低了总体积极情绪极性。对地方政府区域情绪的细粒度分析发现，尽管在研究期间的大多数日子里主导情绪为积极，但一些地方政府区域经历了从积极到消极的显著情绪变化。本研究还分析了推特上热门话题（如政府政策，如澳大利亚的就业保留计划、封锁、社交距离）以及重点社会事件（如“红宝石公主号”邮轮事件）所传递的情绪动态。结果表明，这些政策和事件确实影响了人们的总体情绪，而且它们在不同阶段对人们总体情绪的影响有所不同。
