Medical education / free open access medical education materials are produced and shared by tens of thousands of tweeters across the world using a range of hashtags. The quantity of information shared makes searching out the most useful information challenging. This summary, one of an occasional series (+), looks at some of the most popular material using some of the most commonly used hashtags, selecting out the most widely disseminated material. The resulting summary is a potentially useful selection of tweets from April 2021, though of course in such lists there are sometimes less useful tweets (e.g. bandwagon jumping, spam, misinformation and disinformation). I have not edited the list further than applying the following rules.
This summary of 49,029 tweets by 14,821	tweeters is based on the following Twitter search "#MedEd OR #FOAMed OR #FOAMrad OR #MedTwitter". I set this running on 31 March 2021 and downloaded it on 1 May, updating data every hour using TAGS (identifying 186,423 tweets and retweets posted during April 2021; these tweets were posted by, were retweeted by, or mentioned 77,168 tweeters). I then reimported the tweet/retweet IDs on 6 May using NodeXL. This file, which included 337,498 edges, was too big to graph in NodeXL, but the main parts of the analysis were completed and could be analysed further(*). Read more on methods on the ScotPublicHealth blog. I am attempting to graph the data using Graphistry instead and will post an update here when available.  
The 49,029 tweets identified had received 138,311 retweets by the time of the NodeXL import on 6 May 2021 (and further import of 11 previously missed tweets on 8 May 2021(*)). Of these retweets, 80% were received by 1,645 tweeters (11.1% of the total tweeters). In contrast, 5,253 (35.4%) tweeters received no retweets. 
The 150 tweets listed below, posted by 105 tweeters, were selected as follows: top 5 tweets for each day of April 2021, ordered chronologically (125/150 of these tweets were also in the top 150 tweets for the full period). I used the top 5 for each day to achieve a spread across a full period (otherwise specific events can dominate tweets). These 150 tweets received a median of 116 retweets (range 50-899; interquartile range 89.5-179.5). The top 30 tweeters (by retweets received) are shown in the table below.
Tweets are sometimes deleted, so it is useful to keep a permanent record of these summaries. You can download a PDF of this summary.
(*) 3341 tweet/ retweet IDs were not captured by initial NodeXL import, of which 127 (11 tweets and 116 retweets) were still retrievable using a TAGS import on 8 May. These 11 tweets were included in the final analysis of NodeXL data. 
(+) Check out previous summary produced a year ago at height of first wave of Covid-19 pandemic.

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