Information flow on COVID-19 over Wikipedia: A case study of 11 languages

Chang-Ryong Jung, I. Hong, Diego Sáez-Trumper, Damin Lee, Jaehyeon Myung, Danu Kim, Jinhyuk Yun, Woo-Sung Jung, M. Cha
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Abstract

Wikipedia has been a critical information source during the COVID-19 pandemic. Analyzing how information is created, edited, and viewed on this platform can help gain new insights for risk communication strategies for the next pandemic. Here, we study the content editor and viewer patterns on the COVID-19 related documents on Wikipedia using a near-complete dataset gathered of 11 languages over 238 days in 2020. Based on the analysis of the daily access and edit logs on the identified Wikipedia pages, we discuss how the regional and cultural closeness factors affect information demand and supply.
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维基百科上关于COVID-19的信息流:以11种语言为例
在COVID-19大流行期间,维基百科一直是一个重要的信息来源。分析如何在这个平台上创建、编辑和查看信息,有助于为下一次大流行的风险沟通战略获得新的见解。在这里,我们使用2020年238天内收集的11种语言的近乎完整的数据集,研究了维基百科上与COVID-19相关文档的内容编辑器和查看器模式。本文通过对维基百科已识别页面的日常访问和编辑日志的分析,探讨了地域和文化亲密性因素对信息需求和供给的影响。
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