The #medlibs Influencers
Top 10 Influential
@alisha764 100 | |
![]() | @nikdett 88 |
![]() | @mehlibrarian 82 |
@jonspoke 73 | |
![]() | @lzipperer 68 |
![]() | @pfanderson 68 |
![]() | @hurstej 67 |
![]() | @krafty 66 |
![]() | @blevinsa 65 |
![]() | @MR_INFO_Mark 56 |
Prolific Tweeters
@alisha764 78 | |
![]() | @lzipperer 30 |
![]() | @pfanderson 25 |
![]() | @mehlibrarian 22 |
![]() | @krafty 21 |
![]() | @hurstej 21 |
@jonspoke 21 | |
![]() | @nikdett 19 |
![]() | @blevinsa 15 |
![]() | @MR_INFO_Mark 11 |
Highest Impressions
![]() | @pfanderson 270.5K |
![]() | @krafty 47.2K |
![]() | @ColeFACHE 46.2K |
![]() | @hurstej 43.3K |
![]() | @nikdett 27.4K |
![]() | @mehlibrarian 25.4K |
![]() | @lzipperer 23.0K |
![]() | @MR_INFO_Mark 22.8K |
![]() | @blevinsa 11.5K |
![]() | @lwu5 2.2K |
The Numbers
29.957KImpressions309Tweets
23Participants
247Avg 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