Your browser doesn't support javascript.
Country Image in COVID-19 Pandemic: A Case Study of China.
Chen, Huimin; Zhu, Zeyu; Qi, Fanchao; Ye, Yining; Liu, Zhiyuan; Sun, Maosong; Jin, Jianbin.
  • Chen H; School of Journalism and CommunicationTsinghua University Beijing 100084 China.
  • Zhu Z; School of Journalism and CommunicationTsinghua University Beijing 100084 China.
  • Qi F; Department of Computer Science and TechnologyTsinghua University Beijing 100084 China.
  • Ye Y; Department of Computer Science and TechnologyTsinghua University Beijing 100084 China.
  • Liu Z; Department of Computer Science and TechnologyTsinghua University Beijing 100084 China.
  • Sun M; Department of Computer Science and TechnologyTsinghua University Beijing 100084 China.
  • Jin J; School of Journalism and CommunicationTsinghua University Beijing 100084 China.
IEEE Trans Big Data ; 7(1): 81-92, 2021 Mar 01.
Article in English | MEDLINE | ID: covidwho-1138050
ABSTRACT
Country image has a profound influence on international relations and economic development. In the worldwide outbreak of COVID-19, countries and their people display different reactions, resulting in diverse perceived images among foreign public. Therefore, in this article, we take China as a specific and typical case and investigate its image with aspect-based sentiment analysis on a large-scale Twitter dataset. To our knowledge, this is the first study to explore country image in such a fine-grained way. To perform the analysis, we first build a manually-labeled Twitter dataset with aspect-level sentiment annotations. Afterward, we conduct the aspect-based sentiment analysis with BERT to explore the image of China. We discover an overall sentiment change from non-negative to negative in the general public, and explain it with the increasing mentions of negative ideology-related aspects and decreasing mentions of non-negative fact-based aspects. Further investigations into different groups of Twitter users, including U.S. Congress members, English media, and social bots, reveal different patterns in their attitudes toward China. This article provides a deeper understanding of the changing image of China in COVID-19 pandemic. Our research also demonstrates how aspect-based sentiment analysis can be applied in social science researches to deliver valuable insights.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report / Experimental Studies / Randomized controlled trials Language: English Journal: IEEE Trans Big Data Year: 2021 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report / Experimental Studies / Randomized controlled trials Language: English Journal: IEEE Trans Big Data Year: 2021 Document Type: Article