Social Media Index (SM-i) – BETA
Academics have created indices to compare both scholars (h-index) and journals (Impact Factor) within a given field. The websites that contribute to the creation of Free Open Access Medical Education (FOAM) do not have a comparable parameter. This makes assessing the impact of each website challenging for both content producers and their supervisors. Additionally, learners may find it difficult to distinguish between reputable and unproven websites.
The Social Media Index (SM-i) was developed to address these problems. It is a comparative index derived from three easily obtainable indicators including: Alexa Rank (of the website), Twitter Followers (of the most prominent editor), and Facebook Likes (of the website’s page). For each website these three indicators are normalized and added together to give a score ranging from 0 to 10. The details of the derivation and validation of the SM-i are outlined in a freely available article recently published in the Western Journal of Emergency Medicine.
Changes in the online world have required further revision to the SMi formula since data collection for the WestJEM article in 2013-14. Specifically, Google has quit updating PageRank which prevents its inclusion in future versions of the SMi. As outlined in the WestJEM article, Alexa correlated quite highly both with metrics of journal impact (when applied to medical journals) and PageRank. Additionally, almost every website had a value. For these reasons we have elected to double the weight of the Alexa Rank in the calculation to replace the contribution of PageRank. The calculation of the Alexa Rank component has also been modified slightly by fixing the lowest ranking websites to a value of 0 for that indicator (this change increases the range of values and makes it more consistent with the other variables). In the future we will be monitoring how these changes affect the SMi in the interests of making it a helpful and user-friendly metric.
Incorporating these changes, the formula used in this version of the SMi is:
Where max = maximum value, min = minimum value, site = value for a particular website.
Notes on the latest update
Thanks to Dr. Puneet Kapur (@kapurp), data for this version of the SMi was collected in November, 2016 by an automated computer program. The rankings from previous iterations (June 2015, November 2016, and June 2016) are included. For those interested in the ongoing development of the SMi, data collection for a study evaluating its ability to predict blog post quality is complete and should be published sometime in 2017.
As this is still a BETA version, we would appreciate your assistance in correcting any errors (Did we miss an Alexa Rank, Twitter Account, or Facebook page? Is our data inaccurate?). Feedback on the SMi can also be provided by commenting on this page, commenting on blog posts about the SMi, e-mailing Brent Thoma, or tweeting @Brent_Thoma.[table id=165 /]
*Sites without an Alexa Rank score were given the maximum rank (the same as the lowest ranked website).