Analysis of Twitter Data Using Evolutionary Clustering during the COVID-19 Pandemic
Analysis of Twitter Data Using Evolutionary Clustering during the COVID-19 Pandemic
复制标题
DOI：
10.32604/cmc.2020.011489
复制
发表时间：
2020-01-01
影响因子：
3.1
通讯作者：
Hassanien, Aboul Ella
中科院分区：
文献类型：
--
作者：
Arpaci, Ibrahim;Alshehabi, Shadi;Hassanien, Aboul Ella
新型冠状病毒（COVID-19）一出现，人们就开始在Twitter上发布文本推文。分析这些推文可以帮助机构更好地决策和优先考虑他们的任务。因此，这项研究旨在分析2020年3月22日至3月30日期间收集的4300万条推文，并使用进化聚类分析描述公众对COVID-19疫情相关话题的关注趋势。结果表明，一元词比二元词和三元词的趋势更频繁。疫情期间，大量关于COVID-19的推文被传播并受到公众的广泛关注。“死亡”、“检测”、“传播”、“封锁”等高频词表明，人们害怕被感染，而被感染的人害怕死亡。调查结果还显示，由于担心传播，人们同意呆在家里，自从他们意识到COVID-19以来，他们呼吁保持社交距离。可以认为，社交媒体帖子可能会影响人类的心理和行为。这些结果可能有助于政府和卫生组织更好地了解公众的心理，从而更好地与他们沟通，以预防和管理恐慌。
People started posting textual tweets on Twitter as soon as the novel coronavirus (COVID-19) emerged. Analyzing these tweets can assist institutions in better decision-making and prioritizing their tasks. Therefore, this study aimed to analyze 43 million tweets collected between March 22 and March 30, 2020 and describe the trend of public attention given to the topics related to the COVID-19 epidemic using evolutionary clustering analysis. The results indicated that unigram terms were trended more frequently than bigram and trigram terms. A large number of tweets about the COVID-19 were disseminated and received widespread public attention during the epidemic. The high-frequency words such as "death", "test", "spread", and "lockdown" suggest that people fear of being infected, and those who got infection are afraid of death. The results also showed that people agreed to stay at home due to the fear of the spread, and they were calling for social distancing since they become aware of the COVID-19. It can be suggested that social media posts may affect human psychology and behavior. These results may help governments and health organizations to better understand the psychology of the public, and thereby, better communicate with them to prevent and manage the panic.