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Analysis and visualization of COVID-19 discourse on Twitter using data science: a case study of the USA, the UK and India

机译:分析和可视化COVID-19话语在Twitter上使用数据科学:一个案例研究美国、英国和印度

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Purpose - This paper aims to understand, examine and interpret the main concerns and emotions of the people regarding COVID-19 pandemic in the UK, the USA and India using Data Science measures.Design/methodology/approach - This study implements unsupervised and supervised machine learning methods. i.e. topic modeling and sentiment analysis on Twitter data for extracting the topics of discussion and calculating public sentiment.Findings - Governments and policymakers remained the focus of public discussion on Twitter during the first three months of the pandemic. Overall, public sentiment toward the pandemic remained neutral except for the USA.Originality/value - This paper proposes a Data Science-based approach to better understand the public topics of concern during the COVID-19 pandemic.
机译:目的——本文旨在理解,检查和解释的主要忧虑和情绪人们关于COVID-19大流行性流感在英国,美国和印度使用数据的科学措施。实现无监督和监督机器学习方法。情绪分析在Twitter上提取的数据的话题讨论和计算情绪。仍然是公众讨论的焦点Twitter在前三个月大流行。大流行保持中立除了美国。以科学为基础的方法来更好地理解数据在COVID-19公众关注的话题大流行。

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