About: Social Network Analysis for Coronavirus (COVID‐19) in the United States

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Social Network Analysis for Coronavirus (COVID‐19) in the United States
Creator	Yum, Seungil
Source	Medline; PMC
abstract	OBJECTIVES: This study explores how public key players play an important role in social networks for coronavirus (COVID‐19). METHODS: This study employs social network analyses based on 2,864 Twitter users and 2,775 communications of Twitter. RESULTS: This study finds that President Trump plays the most important role in social networks among the top 20 key players for both in‐degree centrality and content in tweets. Second, Donald Trump and Barak Obama show the opposite result for the in‐degree centrality and follower analysis. The result shows that the topic‐based networks and the person‐based networks play a different role in social networks. This study demonstrates that the presidents, the World Health Organization (WHO) and its regional offices, the Centers for Disease Control, and news channels play a crucial role in the news of COVID‐19 for people. Key players, such as Donald Trump, Barack Obama, and BBC, are located in the central networks. In contrast, U.S. news channels and WHO and its regional offices have independent channels. CONCLUSIONS: Governments should understand the characteristics of public key players to provide information for COVID‐19 in a timely manner.
has issue date	2020-05-28(xsd:dateTime)
bibo:doi	10.1111/ssqu.12808
bibo:pmid	32836475
has license	no-cc
sha1sum (hex)	5d8c66b47ead216dbe41bc81c61259feba89f9e0
schema:url	https://doi.org/10.1111/ssqu.12808
resource representing a document's title	Social Network Analysis for Coronavirus (COVID‐19) in the United States
has PubMed Central identifier	PMC7283848
has PubMed identifier	32836475
schema:publication	Soc Sci Q
resource representing a document's body	covid:5d8c66b47ead216dbe41bc81c61259feba89f9e0#body_text
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