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Knowledge management for extreme public health events COVID-19: based on Tiktok data
Journal of Knowledge Management ; ahead-of-print(ahead-of-print):16, 2021.
Article in English | Web of Science | ID: covidwho-1550694
ABSTRACT
Purpose Taking the COVID-19 as the background, this study aims to investigate the direct influencing factors regarding knowledge sharing behavior (KSB) on new media platforms and discuss how the characteristics of the users could enhance the KSB through moderation effect, and provide empirical evidences. Design/methodology/approach Based on the social exchange theory and after the text analysis of the data collected from the Tiktok platform in 2020, this paper uses the quantitative method to evaluate the factors influence KSB on short video social platform during the COVID-19 outbreak. Findings KSB on new media platform could be enhanced by richer knowledge content of the video posted and the attribute of the platform users directly. Platform users could affect the trustworthiness of the knowledge shared, thus influence the knowledge sharing. On the early stage of the COVID-19, the richer content of the knowledge released by users could effectively enhance the KSB. On the early stage of the emergency events, the official users could play a significant role on KS. During the mitigation stage of COVID-19, the KSB of the knowledge shared by unofficial users with richer content could be enhanced and the moderation effect is relatively stronger. Originality/value The research extends the social exchange theory to a disaster management context. The authors provide an effective reference for future governments to effectively cope with the epidemic and spread public knowledge in an emergency response context. By analyzing the influence of knowledge content and influencer characteristics, it could help the social media platform to improve content management and optimize resource allocation.

Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Journal of Knowledge Management Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Journal of Knowledge Management Year: 2021 Document Type: Article