  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 webpages to their source evidence. From 207,538 eligible
vaccination-related PubMed articles, we evaluated several approaches using
3,573 unique links to webpages from Altmetric. We evaluated methods for ranking
the source articles for vaccine-related research described on webpages,
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 webpages 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 webpages 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 webpages are
potentially feasible and may support the prevention of bias and
misrepresentation of research in news and social media.
