TY - JOUR
T1 - ‘WP2Cochrane’, a tool linking Wikipedia to the Cochrane Library
T2 - Results of a bibliometric analysis evaluating article quality and importance
AU - Joorabchi, Arash
AU - Doherty, Cailbhe
AU - Dawson, Jennifer
N1 - Publisher Copyright:
© The Author(s) 2019.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - Medical information on English Wikipedia was accessed over 2 billion times in 2018. Our goal was to develop an automated system to assist Wikipedia volunteers to improve articles with high-quality sources from journals such as The Cochrane Library. We created an automated indexing system by linking available reviews from the Cochrane library with disease-related Wikipedia articles and evaluating the relationship between the quality and importance of these articles with the number of relevant and cited Cochrane reviews. We first conducted a bibliometric analysis, identifying disease-related Wikipedia articles and relevant/cited Cochrane reviews. Citations were thematically coded, and descriptive statistics were calculated. Finally, separate multinomial logistic regression analyses were conducted for article quality and importance. The indexing system identified 4381 disease-related Wikipedia articles, 1193 (27%) of which cited a Cochrane review. Higher quality Wikipedia articles were more likely to cite a Cochrane review (p = 0.002), while lower quality articles were less likely to cite a Cochrane review (p < 0.0005). A greater number of Cochrane reviews are available for more ‘important’ Wikipedia articles (p < 0.005), and these articles were more likely to cite a Cochrane review (p < 0.005). This approach to an indexing system can be leveraged by Wikipedia contributors and editors seeking to update disease-related Wikipedia articles with relevant Cochrane reviews (thus improving their quality), and online information seekers in need of additional information to supplement their Wikipedia search.
AB - Medical information on English Wikipedia was accessed over 2 billion times in 2018. Our goal was to develop an automated system to assist Wikipedia volunteers to improve articles with high-quality sources from journals such as The Cochrane Library. We created an automated indexing system by linking available reviews from the Cochrane library with disease-related Wikipedia articles and evaluating the relationship between the quality and importance of these articles with the number of relevant and cited Cochrane reviews. We first conducted a bibliometric analysis, identifying disease-related Wikipedia articles and relevant/cited Cochrane reviews. Citations were thematically coded, and descriptive statistics were calculated. Finally, separate multinomial logistic regression analyses were conducted for article quality and importance. The indexing system identified 4381 disease-related Wikipedia articles, 1193 (27%) of which cited a Cochrane review. Higher quality Wikipedia articles were more likely to cite a Cochrane review (p = 0.002), while lower quality articles were less likely to cite a Cochrane review (p < 0.0005). A greater number of Cochrane reviews are available for more ‘important’ Wikipedia articles (p < 0.005), and these articles were more likely to cite a Cochrane review (p < 0.005). This approach to an indexing system can be leveraged by Wikipedia contributors and editors seeking to update disease-related Wikipedia articles with relevant Cochrane reviews (thus improving their quality), and online information seekers in need of additional information to supplement their Wikipedia search.
KW - Bibliometrics [MeSH]
KW - Encyclopedias as Topic [MeSH]
KW - Internet
KW - knowledge translation
KW - open knowledge
KW - peer review
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=85077141675&partnerID=8YFLogxK
U2 - 10.1177/1460458219892711
DO - 10.1177/1460458219892711
M3 - Article
C2 - 31868082
AN - SCOPUS:85077141675
SN - 1460-4582
VL - 26
SP - 1881
EP - 1897
JO - Health Informatics Journal
JF - Health Informatics Journal
IS - 3
ER -