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COVID-19 Tweet Links: A Preliminary Investigation of Type and Relevance.
Goh, Dion Hoe-Lian; Lee, Chei Sian; Zheng, Han; Theng, Yin Leng.
  • Goh DH; Nanyang Technological University Singapore.
  • Lee CS; Nanyang Technological University Singapore.
  • Zheng H; Nanyang Technological University Singapore.
  • Theng YL; Nanyang Technological University Singapore.
Proc Assoc Inf Sci Technol ; 59(1): 693-695, 2022.
Article in English | MEDLINE | ID: covidwho-2260820
ABSTRACT
We conducted an exploratory study of the links found in Twitter tweets. Our results showed that the largest category of tweet links was social media platforms followed by alternative news sites. Government agencies and educational institutions were under-represented. In terms of relevance, about 75% of the links were related to COVID-19 but disappointingly, only 40% of the links were directly related to their respective tweets' topics.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Proc Assoc Inf Sci Technol Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Proc Assoc Inf Sci Technol Year: 2022 Document Type: Article