Social Media Index (SMi)
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 (SMi) 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)
- Facebook Likes (of the website’s page)
For each website, these 3 indicators are normalized and added together to give a score ranging from 0 to 10. The details of the derivation and validation of the SMi are outlined in the Western Journal of Emergency Medicine1 while a study investigating the SMi’s correlation with quality has recently been published in Annals of Emergency Medicine.2
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 or tweeting @Brent_Thoma.
Update: Removal of PageRank
Google deprecated the PageRank metric after our original publication1 in 2013. Because of this, PageRank will no longer be included in future versions of the SMi.
Fortunately, our data in the 2013 WestJEM paper suggests that the Alexa score has a high correlation to PageRank. Because of this, we have elected to double the weight of the Alexa score in the SMi calculation to replace PageRank’s contribution. We have also modified the calculation of the Alexa component of the SMi. This change fixes the lowest ranking websites to a value of 0, which increases the range of values. The effect of this change makes the score more consistent with the other components. The current formula has been shown to correlate with quality.2
The detailed formula is:
Where max = maximum value, min = minimum value, site = value for a particular website.