The global spread of COVID-19 has caused pandemics to be widely discussed. This is evident in the large number of scientific articles and the amount of user-generated content on social media. This paper aims to compare academic communication and social communication about the pandemic from the perspective of communication preference differences. It aims to provide information for the ongoing research on global pandemics, thereby eliminating knowledge barriers and information inequalities between the academic and the social communities. First, we collected the full text and the metadata of pandemic-related articles and Twitter data mentioning the articles. Second, we extracted and analyzed the topics and sentiment tendencies of the articles and related tweets. Finally, we conducted pandemic-related differential analysis on the academic community and the social community. We mined the resulting data to generate pandemic communication preferences (e.g., information needs, attitude tendencies) of researchers and the public, respectively. The research results from 50,338 articles and 927,266 corresponding tweets mentioning the articles revealed communication differences about global pandemics between the academic and the social communities regarding the consistency of research recognition and the preferences for particular research topics. The analysis of large-scale pandemic-related tweets also confirmed the communication preference differences between the two communities.
翻译:COVID-19的全球传播导致广泛讨论流行病问题,这表现在大量科学文章以及社交媒体上用户产生的大量内容上,本文件旨在从传播偏好差异的角度比较关于这一大流行病的学术交流和社会交流,目的是为正在进行的全球大流行病研究提供信息,从而消除学术界和社会界之间的知识障碍和信息不平等。首先,我们收集了与大流行病有关的文章全文和元数据以及提及文章的Twitter数据。第二,我们提取并分析了文章和有关推文的主题和情绪趋势。最后,我们对学术界和社会界进行了与大流行病有关的差异分析。我们利用由此产生的数据,分别产生了研究人员和公众的大流行病传播偏好(例如信息需求、态度倾向)。50,338篇文章和927,266条对应的推文的研究结果揭示了学术界和社会界之间在研究认知的一致性和对特定研究专题的偏好方面存在的沟通差异。对大规模大流行病相关的推文的分析也证实了两个社区之间的通信偏好差异。