The #medlibs Influencers
Top 10 Influential
![]() | @mascher 100 |
![]() | @mehlibrarian 99 |
![]() | @pfanderson 89 |
@s_schulte 85 | |
![]() | @nikdett 82 |
![]() | @krafty 80 |
![]() | @rachel_w 79 |
![]() | @CarolinaFan1982 58 |
![]() | @nrglassman 40 |
![]() | @LaMedBoheme73 35 |
Prolific Tweeters
![]() | @pfanderson 63 |
![]() | @mehlibrarian 30 |
![]() | @nikdett 25 |
![]() | @mascher 24 |
![]() | @rachel_w 16 |
![]() | @CarolinaFan1982 11 |
![]() | @krafty 10 |
![]() | @7shores 10 |
@s_schulte 8 | |
@mscully66 6 |
Highest Impressions
![]() | @pfanderson 681.8K |
![]() | @rachel_w 47.7K |
![]() | @nikdett 36.0K |
![]() | @mehlibrarian 34.6K |
![]() | @mascher 23.5K |
![]() | @krafty 22.5K |
![]() | @7shores 12.6K |
![]() | @CarolinaFan1982 11.6K |
![]() | @mandosally 3.4K |
![]() | @fowlerbird 1.4K |
The Numbers
26.605KImpressions216Tweets
17Participants
173Avg 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