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

Authors:

Woo-Sung Jung, and

Meeyoung ChaAuthors Info & Claims

WWW '21: Companion Proceedings of the Web Conference 2021

April 2021

Pages 627 - 628

https://doi.org/10.1145/3442442.3452352

Published: 03 June 2021 Publication History

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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.

References

[1]

Giovanni Colavizza. 2020. COVID-19 research in Wikipedia. Quantitative Science Studies 1, 4 (2020), 1349–1380. https://doi.org/10.1162/qss_a_00080

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[2]

Changwook Jung, Diego Saez-Trumper, Inho Hong, and Meeyoung Cha. 2020. COVID-19 Wikipedia data. https://doi.org/10.6084/m9.figshare.13239515.v4

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[3]

Robert R Sokal. 1958. A statistical method for evaluating systematic relationships.Univ. Kansas, Sci. Bull. 38 (1958), 1409–1438.

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John Zarocostas. 2020. How to fight an infodemic. The lancet 395, 10225 (2020), 676.

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Published In

WWW '21: Companion Proceedings of the Web Conference 2021

April 2021

726 pages

ISBN:9781450383134

DOI:10.1145/3442442

Editors:
Jure Leskovec
Stanford
,
Marko Grobelnik
Jožef Stefan Institute
,
Marc Najork
Google
,
Jie Tang
Tsinghua University
,
Leila Zia
Wikimedia Foundation

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 03 June 2021

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SIGWEB

WWW '21: The Web Conference 2021

April 19 - 23, 2021

Ljubljana, Slovenia

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Extracting complementary information from Wikipedia articles of different languages

Good quality complementary information for multilingual wikipedia

Information asymmetry in Wikipedia across different languages: A statistical analysis

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