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 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 five 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.


翻译:2019年科罗纳病毒疾病(COVID-19)的爆发对全世界人民的日常生活产生了前所未有的影响,各国政府在大流行病期间实施了各种防治疾病的措施和政策,如封锁和社会分裂等。这些措施和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Twitter用户张贴的大量文本数据,分析澳大利亚新南威尔士州(新南威尔士州)居民在大流行病期间的情绪动态。不同于目前主要侧重于国家一级和静态情绪分析的工作,我们分析了精细的地方政府地区(LGAs)的情绪动态。根据对大约183 000个用户在五个月中在新南威尔士州不同地方政府(LGAs)张贴的大约9 400万个推特进行的分析,我们发现新南威尔士州民众表现出了总体的情感极性,而COVID-19大流行则降低了总体的情感极性。 精细分析LGAs的情绪变化对总体的情绪变化和情绪变化也表现为真实性。

0
下载
关闭预览

相关内容

专知会员服务
123+阅读 · 2020年9月8日
因果图,Causal Graphs,52页ppt
专知会员服务
243+阅读 · 2020年4月19日
【深度学习视频分析/多模态学习资源大列表】
专知会员服务
91+阅读 · 2019年10月16日
[综述]深度学习下的场景文本检测与识别
专知会员服务
77+阅读 · 2019年10月10日
无人机视觉挑战赛 | ICCV 2019 Workshop—VisDrone2019
PaperWeekly
7+阅读 · 2019年5月5日
已删除
将门创投
3+阅读 · 2019年4月19日
【计算机类】期刊专刊/国际会议截稿信息6条
Call4Papers
3+阅读 · 2017年10月13日
Arxiv
5+阅读 · 2015年9月14日
VIP会员
相关资讯
无人机视觉挑战赛 | ICCV 2019 Workshop—VisDrone2019
PaperWeekly
7+阅读 · 2019年5月5日
已删除
将门创投
3+阅读 · 2019年4月19日
【计算机类】期刊专刊/国际会议截稿信息6条
Call4Papers
3+阅读 · 2017年10月13日
Top
微信扫码咨询专知VIP会员