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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Guang, Lu | - |
| dc.contributor.author | Martin, Businger | - |
| dc.contributor.author | Christian, Dollfus | - |
| dc.date.accessioned | 2023-04-10T06:46:44Z | - |
| dc.date.available | 2023-04-10T06:46:44Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s41060-022-00364-7 | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7724 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | Over the past two years, organizations and businesses have been forced to constantly adapt and develop effective responses to the challenges of the COVID-19 pandemic. The acuteness, global scale and intense dynamism of the situation make online news and information even more important for making informed management and policy decisions. This paper focuses on the economic impact of the COVID-19 pandemic, using natural language processing (NLP) techniques to examine the news media as the main source of information and agenda-setters of public discourse over an eight-month period. | vi |
| dc.language.iso | en | vi |
| dc.publisher | Springer | vi |
| dc.subject | challenges of the COVID-19 pandemic | vi |
| dc.subject | using natural language processing (NLP) technique | vi |
| dc.title | Agenda-Setting for COVID-19 A Study of Large-Scale Economic News Coverage Using Natural Language Processing | vi |
| dc.type | Book | vi |
| Appears in Collections | ||
| OER - Công nghệ thông tin | ||
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