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Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis

BACKGROUND: In the current era of widespread access to the internet, we can monitor public interest in a topic via information-targeted web browsing. We sought to provide direct proof of the global population’s altered use of Wikipedia medical knowledge resulting from the new COVID-19 pandemic and r...

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Detalles Bibliográficos
Autores principales: Chrzanowski, Jędrzej, Sołek, Julia, Fendler, Wojciech, Jemielniak, Dariusz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049630/
https://www.ncbi.nlm.nih.gov/pubmed/33667176
http://dx.doi.org/10.2196/26331
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author Chrzanowski, Jędrzej
Sołek, Julia
Fendler, Wojciech
Jemielniak, Dariusz
author_facet Chrzanowski, Jędrzej
Sołek, Julia
Fendler, Wojciech
Jemielniak, Dariusz
author_sort Chrzanowski, Jędrzej
collection PubMed
description BACKGROUND: In the current era of widespread access to the internet, we can monitor public interest in a topic via information-targeted web browsing. We sought to provide direct proof of the global population’s altered use of Wikipedia medical knowledge resulting from the new COVID-19 pandemic and related global restrictions. OBJECTIVE: We aimed to identify temporal search trends and quantify changes in access to Wikipedia Medicine Project articles that were related to the COVID-19 pandemic. METHODS: We performed a retrospective analysis of medical articles across nine language versions of Wikipedia and country-specific statistics for registered COVID-19 deaths. The observed patterns were compared to a forecast model of Wikipedia use, which was trained on data from 2015 to 2019. The model comprehensively analyzed specific articles and similarities between access count data from before (ie, several years prior) and during the COVID-19 pandemic. Wikipedia articles that were linked to those directly associated with the pandemic were evaluated in terms of degrees of separation and analyzed to identify similarities in access counts. We assessed the correlation between article access counts and the number of diagnosed COVID-19 cases and deaths to identify factors that drove interest in these articles and shifts in public interest during the subsequent phases of the pandemic. RESULTS: We observed a significant (P<.001) increase in the number of entries on Wikipedia medical articles during the pandemic period. The increased interest in COVID-19–related articles temporally correlated with the number of global COVID-19 deaths and consistently correlated with the number of region-specific COVID-19 deaths. Articles with low degrees of separation were significantly similar (P<.001) in terms of access patterns that were indicative of information-seeking patterns. CONCLUSIONS: The analysis of Wikipedia medical article popularity could be a viable method for epidemiologic surveillance, as it provides important information about the reasons behind public attention and factors that sustain public interest in the long term. Moreover, Wikipedia users can potentially be directed to credible and valuable information sources that are linked with the most prominent articles.
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spelling pubmed-80496302021-04-22 Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis Chrzanowski, Jędrzej Sołek, Julia Fendler, Wojciech Jemielniak, Dariusz J Med Internet Res Original Paper BACKGROUND: In the current era of widespread access to the internet, we can monitor public interest in a topic via information-targeted web browsing. We sought to provide direct proof of the global population’s altered use of Wikipedia medical knowledge resulting from the new COVID-19 pandemic and related global restrictions. OBJECTIVE: We aimed to identify temporal search trends and quantify changes in access to Wikipedia Medicine Project articles that were related to the COVID-19 pandemic. METHODS: We performed a retrospective analysis of medical articles across nine language versions of Wikipedia and country-specific statistics for registered COVID-19 deaths. The observed patterns were compared to a forecast model of Wikipedia use, which was trained on data from 2015 to 2019. The model comprehensively analyzed specific articles and similarities between access count data from before (ie, several years prior) and during the COVID-19 pandemic. Wikipedia articles that were linked to those directly associated with the pandemic were evaluated in terms of degrees of separation and analyzed to identify similarities in access counts. We assessed the correlation between article access counts and the number of diagnosed COVID-19 cases and deaths to identify factors that drove interest in these articles and shifts in public interest during the subsequent phases of the pandemic. RESULTS: We observed a significant (P<.001) increase in the number of entries on Wikipedia medical articles during the pandemic period. The increased interest in COVID-19–related articles temporally correlated with the number of global COVID-19 deaths and consistently correlated with the number of region-specific COVID-19 deaths. Articles with low degrees of separation were significantly similar (P<.001) in terms of access patterns that were indicative of information-seeking patterns. CONCLUSIONS: The analysis of Wikipedia medical article popularity could be a viable method for epidemiologic surveillance, as it provides important information about the reasons behind public attention and factors that sustain public interest in the long term. Moreover, Wikipedia users can potentially be directed to credible and valuable information sources that are linked with the most prominent articles. JMIR Publications 2021-04-12 /pmc/articles/PMC8049630/ /pubmed/33667176 http://dx.doi.org/10.2196/26331 Text en ©Jędrzej Chrzanowski, Julia Sołek, Wojciech Fendler, Dariusz Jemielniak. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.04.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Chrzanowski, Jędrzej
Sołek, Julia
Fendler, Wojciech
Jemielniak, Dariusz
Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis
title Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis
title_full Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis
title_fullStr Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis
title_full_unstemmed Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis
title_short Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak: Search Trends Analysis
title_sort assessing public interest based on wikipedia’s most visited medical articles during the sars-cov-2 outbreak: search trends analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8049630/
https://www.ncbi.nlm.nih.gov/pubmed/33667176
http://dx.doi.org/10.2196/26331
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