Skip Nav Destination
1-1 of 1
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Publisher: Journals Gateway
Quantitative Science Studies (2020) 1 (2): 810–823.
Published: 01 June 2020
FIGURES | View All (5)
AbstractView article PDF
Online health communications often provide biased interpretations of evidence and have unreliable links to the source research. We tested the feasibility of a tool for matching web pages to their source evidence. From 207,538 eligible vaccination-related PubMed articles, we evaluated several approaches using 3,573 unique links to web pages from Altmetric. We evaluated methods for ranking the source articles for vaccine-related research described on web pages, comparing simple baseline feature representation and dimensionality reduction approaches to those augmented with canonical correlation analysis (CCA). Performance measures included the median rank of the correct source article; the percentage of web pages for which the source article was correctly ranked first (recall@1); and the percentage ranked within the top 50 candidate articles (recall@50). While augmenting baseline methods using CCA generally improved results, no CCA-based approach outperformed a baseline method, which ranked the correct source article first for over one quarter of web pages and in the top 50 for more than half. Tools to help people identify evidence-based sources for the content they access on vaccination-related web pages are potentially feasible and may support the prevention of bias and misrepresentation of research in news and social media.