更正:推文能预测引用量吗?基于Twitter的社会影响度量及其与传统科学影响度量的相关性

Eysenbach (J Med Internet Res 2011;13[4]:e123)最初发表版本的社论中关于引用和推文之间关系的参考文献部分的一个小错误已被纠正;此外，作为数据集一部分的引用不再作为“引用”引用。现在更正的参考文献问题只是一个“格式/演示”问题，对研究结果没有影响。最初发表的文章正确地指出，在3/2009期和2/2010期之间发表的所有55篇文章都被包括在内，但引用的参考文献错误地包含了12篇来自2/2009期的额外参考文献，由于文章中描述的原因(issue 3/2009前的稀疏推文)，这些文献不属于分析的一部分。在修正版中，我们不仅删除了这额外的12篇参考文献(31-42篇)，而且我们还利用这个机会将所收录文章的所有其他参考文献(43-97篇)移到了新的多媒体附录2中，不再在“参考文献”部分引用它们。我们现在在论文中通过文章ID (DOI的最后4位数字)来引用它们，我们以前使用的是文本引用(表2和讨论)。虽然之前引用文章的方式没有问题，虽然我们认为引用我们在论文中讨论的影响的JMIR文章是适当和必要的，但我们希望避免任何潜在的印象，即这篇社论人为地歪曲了JMIR未来的影响因子。避免这种情况的一种方法是将引用移动到单独的文件中。最初决定引用它们作为参考文献是为了方便我们的读者，以防止他们不得不在单独的文件或DOI中查找参考文献。JMIR没有空间限制，通常更喜欢在文章中而不是在附录中引用参考文献; for readers downloading a PDF file it is more convenient to have all references in a single file rather than having to download a separate Appendix. The decision to now move these references into a Multimedia Appendix was made after a reader and publishing colleague pointed out that citing these articles may increase JMIR’s impact factor. Although none of the two peer-reviewers, both experts in scientometrics, were originally concerned about citing the included articles as references, and even though any potential additional impact factor points after the decimal point caused by the original editorial would probably have been neglible (after all, these articles are already highly cited: altogether, 638 times, according to Google Scholar), and even though Thomson Reuters also publishes a journal impact factor that excludes journal self-citations, we wish to avoid any potential debate or uncertainty on what proportion of future JMIR impact factors were caused by this editorial, and have therefore decided to pre-emptively move these references into a separate file (Multimedia Appendix 2). The article correction was made on January 4, 2012, before submission to PubMed Central, Swets and other content aggregators and databases, and before indexing by Thomson Reuters. Having to remove references from a manuscript to preserve the validity of a journal-level impact metric is somewhat troubling, but if anything, then this perhaps illustrates the limitations and tyranny of the impact factor, and why we should consider additional metrics.