The #medlibs Influencers
Top 10 Influential
![]() | @blevinsa 100 |
![]() | @mascher 95 |
![]() | @krafty 91 |
![]() | @nikdett 86 |
![]() | @mehlibrarian 84 |
![]() | @aldricham 81 |
![]() | @pfanderson 69 |
![]() | @btuttle 24 |
![]() | @CarolinaFan1982 20 |
@alisha764 20 |
Prolific Tweeters
![]() | @mascher 40 |
![]() | @pfanderson 22 |
![]() | @krafty 22 |
![]() | @nikdett 19 |
![]() | @mehlibrarian 18 |
![]() | @blevinsa 16 |
@mscully66 12 | |
@alisha764 5 | |
![]() | @mandosally 3 |
![]() | @CarolinaFan1982 2 |
Highest Impressions
![]() | @pfanderson 238.1K |
![]() | @krafty 49.5K |
![]() | @mascher 39.2K |
![]() | @nikdett 27.4K |
![]() | @mehlibrarian 20.8K |
![]() | @blevinsa 12.3K |
![]() | @healthtechhatch 7.2K |
![]() | @mandosally 5.1K |
@mscully66 2.4K | |
![]() | @CarolinaFan1982 2.1K |
The Numbers
28.036KImpressions161Tweets
12Participants
129Avg Tweets/Hour
13Avg Tweets/Participant
Twitter data from the #medlibs hashtag from to () โ Symplur.
Top 10 Influencers is determined by the SymplurRank algorithm.
#medlibs Participants










Data for #medlibs can be up to 15 minutes delayed