The #medlibs Influencers
Top 10 Influential
![]() | @nikdett 100 |
![]() | @mehlibrarian 96 |
![]() | @pfanderson 94 |
![]() | @krafty 93 |
![]() | @tlknott 93 |
![]() | @BerrymanD 76 |
@davidlrothman 72 | |
![]() | @mascher 72 |
![]() | @TBrigham 66 |
@evelevemelton 62 |
Prolific Tweeters
![]() | @pfanderson 50 |
![]() | @mehlibrarian 49 |
![]() | @nikdett 36 |
![]() | @krafty 24 |
![]() | @BerrymanD 20 |
![]() | @mascher 19 |
![]() | @tlknott 17 |
@davidlrothman 14 | |
![]() | @7shores 12 |
@RyloLH 9 |
Highest Impressions
![]() | @pfanderson 541.2K |
![]() | @mehlibrarian 56.5K |
![]() | @krafty 54.0K |
![]() | @nikdett 51.9K |
![]() | @mascher 18.6K |
![]() | @tlknott 16.9K |
![]() | @7shores 15.1K |
![]() | @rachel_w 14.9K |
![]() | @mandosally 10.1K |
![]() | @BerrymanD 9.6K |
The Numbers
24.915KImpressions276Tweets
17Participants
221Avg Tweets/Hour
16Avg 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