School of Technology, University of Wolverhampton, Wolverhampton, United Kingdom.
PLoS One. 2013 May 28;8(5):e64841. doi: 10.1371/journal.pone.0064841. Print 2013.
Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.
来自社交网络的 Altmetric 计量指标越来越被提倡和用作文章影响力和实用性的早期指标。然而,尽管有一些案例研究报告了特定的 Altmetric 指标与期刊或领域的引文率之间存在中等相关性,但缺乏系统的科学证据表明 Altmetric 是影响力或实用性的有效替代指标。为了填补这一空白,本研究比较了 11 种 Altmetric 指标与 Web of Science 引文,涉及 76 至 208,739 篇 PubMed 文章,其中每篇文章至少有一条 Altmetric 提及,每个指标最多涉及 1,891 种期刊。它还引入了一个简单的符号检验来克服由于不同的引文和使用窗口引起的偏差。在所有情况下,除了 Google+帖子外,对于具有积极 Altmetric 分数的文章,较高的指标分数与较高的引文之间都存在统计学上显著的关联,这些情况有足够的证据(Twitter、Facebook 墙贴、研究亮点、博客、主流媒体和论坛)。对于 LinkedIn、Pinterest、问答网站和 Reddit,证据不足,对于具有零 Altmetric 分数的文章或 Altmetric 和引文之间的任何相关性的强度,都不应得出任何结论。尽管如此,即使在同一年,对于不同时间发表的文章的引文和指标值之间的比较也可以消除或反转这种关联,因此,出版商和科学计量学家在使用 Altmetric 对文章进行排名时应考虑时间的影响。最后,除了 Twitter 之外,所有 Altmetric 的覆盖范围似乎都很低,因此不清楚它们是否足够普遍,是否可以在实践中发挥作用。