The #medlibs Influencers
Top 10 Influential
![]() | @pfanderson 100 |
@quasifesto 83 | |
![]() | @mehlibrarian 82 |
![]() | @aldricham 82 |
@s_schulte 76 | |
![]() | @mascher 71 |
![]() | @nikdett 70 |
![]() | @krafty 65 |
@howval 58 | |
![]() | @lzipperer 49 |
Prolific Tweeters
![]() | @pfanderson 57 |
![]() | @mehlibrarian 42 |
![]() | @nikdett 31 |
![]() | @mascher 22 |
@quasifesto 14 | |
@s_schulte 12 | |
![]() | @7shores 10 |
![]() | @TBrigham 8 |
![]() | @krafty 7 |
@mscully66 6 |
Highest Impressions
![]() | @pfanderson 616.8K |
![]() | @mehlibrarian 48.4K |
![]() | @FutureDocs 47.8K |
![]() | @nikdett 44.7K |
![]() | @mascher 21.6K |
![]() | @krafty 15.7K |
![]() | @JaneBozarth 15.7K |
![]() | @7shores 12.6K |
![]() | @SafetyNurse 8.4K |
![]() | @BrianSMcGowan 4.1K |
The Numbers
100.717KImpressions230Tweets
25Participants
184Avg Tweets/Hour
9Avg 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