How online usage of subscription‐based journalism and mass communication research journal articles predicts citations
Publication
, Journal Article
Ha, L; Jiang, W; Bi, C; Zhang, R; Zhang, T; Wen, X
Published in: Learned Publishing
This study examines the predicting power of content and non‐content article attributes and of total online usage on short‐term citations of subscription‐based journal articles. It examines articles published in () between 2012 and 2014. The results indicate that the total online usage (full article and abstract page views and article downloads) can be a very strong predictor for citations and can even wipe out the effects of hot topics. Mobile and social media are the media of study most cited in the articles studied. There is no identifiable gender citation gap as authors of both genders equally enjoy their share in the top 10 most cited list. The only gender‐related finding is that female authors dominate gender‐related topics. We conclude that journal publishers wishing to obtain a quick proxy measure of citation potential for journal articles should consult their total online usage. Furthermore, due to the prevalent bias on topics regarding citation frequency, administrators and librarians are highly advised to take topics into consideration when determining scholars’ citation performance.
