Does Social Media have an Impact Factor?

Abstract

Introduction: Social media is now an everyday part of modern life including medicine. There are an increasing number of healthcare professionals and institutions using social media in their clinical and academic practice1. One study alone in 2011 showed 90% of doctors used social media personally and 65% professionally2. Twitter provides a platform for signposting users to the most current and useful material and provide scope for alternative metrics. Historically, a healthcare professional would use the journal impact factor (JIF) of a journal to select the most appropriate to subscribe to and read, however in today's digital society, Twitter provides the ability to see updates across a range of journals and for the clinician to select what is most relevant for them. We therefore performed an observational study to assess whether there was a correlation between Twitter follower numbers (TFN) and JIF. Methods: A search of 10 popular general medicine, general surgery, vascular surgery and interventional radiology journals was performed, namely: Nature, The New England Journal of Medicine, The Lancet, The British Medical Journal (BMJ), The British Journal of Surgery, Circulation, European Journal of Vascular and Endovascular Surgery, Journal of Vascular Surgery (JVS), Journal of Vascular Interventional Radiology and CardioVascular and Interventional Radiology (CVIR). The 2017 JIF stated on their website as of 4th April 2019 was recorded. Of these 7 cited 2017 Journal Citation Reports3 as the source. The JVS and CVIR both stated a JIF that matched 2017 Journal Citation Reports3 but did not cite the source on website. The BMJ had a published 2017 JIF (23.562) that did not match the Journal Citation Reports (23.259)3 [Table 1]. A search of the journals on Twitter was made and the number of followers as of 15:15 GMT on 5th April was noted. Bivariate regression analysis of the TFN as a function of the JIF was undertaken using Minitab 18 statistical software. For the purpose of the analyses the JIF as per the journal website was used, as the minor variations indicated would be likely to have any major impact on the outcomes. Results: There was a visible impression that the higher the JIF the higher the TFN [Table 1]. However, there was low correlation between the JIF and number of followers (adjusted R-sq= 20.76%, p=.104; Graph 1), with occasional low JIF journals also having a large number of followers as noted in the graph outliers. Conclusion: Whilst journals with high JIF clearly had higher TFN, we could find no causal link to suggest that social media following was indeed impacted upon by the impact factor directly. This is likely due to confounding factors particularly the fact that the number of followers will be from a varied background and much higher than that of the number of actual directly contributing authors who are also journal followers, which then via individual and subsequently journal citation impact may possibly have a more direct correlation, but that is outside of the scope of the current analysis.Table 1Journal Impact Factors and Twitter followingGraph 1Scatterplot: correlation between TFN.and JIF.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Disclosure: Nothing to disclose