Article ; Online: Assessing Public Interest Based on Wikipedia’s Most Visited Medical Articles During the SARS-CoV-2 Outbreak
Journal of Medical Internet Research, Vol 23, Iss 4, p e
Search Trends Analysis
2021 Volume 26331
Abstract: ... of entries on Wikipedia medical articles during the pandemic period. The increased interest in COVID-19 ... deaths to identify factors that drove interest in these articles and shifts in public interest during ... a retrospective analysis of medical articles across nine language versions of Wikipedia and country-specific ...
| Abstract | BackgroundIn 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. ObjectiveWe aimed to identify temporal search trends and quantify changes in access to Wikipedia Medicine Project articles that were related to the COVID-19 pandemic. MethodsWe 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. ResultsWe 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. ConclusionsThe analysis of Wikipedia medical article popularity could be a viable method for epidemiologic surveillance, as it provides important information about the ... |
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| Keywords | Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270 |
| Subject code | 028 |
| Language | English |
| Publishing date | 2021-04-01T00:00:00Z |
| Publisher | JMIR Publications |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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