Experimental Biology 2015 Tweet Analysis #expbio

Like 2014 and 2013, I collected tweets for the 2015 Experimental Biology conference (dataset here). The following are some comparisons between the 3 years.

This year, there was an increase in the total number of tweets to the hashtags over the official conference start and end times of 8:00am EST, Saturday March 28 to 4:30pm, Wednesday April 1. The hashtags that were collected were: #xbio, #eb2015, #expbio, #asnatexpbio (this one was added at 10:36pm EST on Saturday, March 28 after I noticed that people were using it). Note: there were small differences in collection methodologies and times between these years but they still reflect a growing interest in twitter use for EB.

Here is the tweet frequency per hour over the official conference time:


Total Tweets Per Year During Experimental Biology

2015 2014 2013
6,720 6,223 5,455

There was also an increase in the number of people who tweeted to the hashtag(s):

Number of Tweeters




Number of Tweeters

Number of Tweeters

Number of Tweeters

1,474 1,278 864

Top 10 Tweeters

2015 2014 2013
Handle Tweet Count Handle Tweet Count Handle Tweet Count
ASBMB 168 ASBMB 226 Biochembelle 292
GMFHx 158 Biochembelle 196 Drdairy50 243
Vdoloughlin 151 Daviddespain 190 ASBMB 223
DrKirtyBrown 120 Drugmonkeyblog 159 Daviddespain 211
JohnCChatham 114 Expbio 112 Bwcorb 185
Profbdcohen 99 cjmetzgarRD 104 LICORBio 122
RajMukhop 98 Nutritionorg 88 DrAmyRD 116
Drugmonkeyblog 96 Drdairy50 81 Nutritionorg 92
Expbio 96 PHLane 77 ChrisPickett5 81
APSPhysiology 91 Paulaike 74 Phyziochick 81

Top 10 Tweets 2015 (+ Retweeted Count)

Tweet Retweeted Count
RT @APSPhysiology: #SciComm words to live by: “Get to the Point Early” – Evonne Kaplan-Liss of the @AldaCenter #ExpBio #APS t.co/v13… 61
RT @StrangeSource: “We do need more PhDs, we just don’t need them after they’re post-docs.” – audience comment w discussion of +ive feedbac… 42
RT @acarrothersRD: “If you don’t translate your science, someone else will do it 4 you. Impt to be engaged in conversation on social media”… 39
RT @daviddespain: “Google doesn’t tell you what the truth is. Google tells you what’s popular.” – @drdairy50 on #scicomm #expbio #eb2015 #A… 31
RT @ConscienHealth: False expectations that “#exercise is a very effective way to lose weight” can lead to discouragement. #EB2015 t… 23
RT @daviddespain: Fritsche says he believed omega-6 LA promoted inflammation, ’til did syst review; found no evidence #expbio #eb2015 http:… 21
RT @drugmonkeyblog: Teitelbaum pointing out that STEM shortage claims are BS and driven by IT companies to get more H1B visas for cheap lab… 20
RT @drugmonkeyblog: Desmond (NIMH PO) – because only 15% of those entering grad school end up in research intensive jobs….we need more. #… 17
RT @StrangeSource: Question from audience: “Does anyone at the NIH know when the boomers plan to retire?” #expbio Heh. 16
RT @NutriciaPsota: “Never say on social media what you wouldn’t say on a crowded elevator” -@lisagualtieri #eb2015 #expbio 15


Hashtag Confusion?

Like last year, there was a change in the official hashtag for EB- previous years have used the #xbio format or #eb2013. Except this year there was additional confusion because the official account promoted #expbio as the hashtag, yet several people reported that within the conference it was advertised on signs as #EB2015.

In addition, orgs like ASN had separate hashtags:

An analysis of the data suggested that people were indeed confused on what to use. Of the 6,720 tweets:

  • 52% (3,492) only contained #expbio
  • 18% (1,198) only contained #eb2015
  • 11% (745) used both #expbio and #eb2015 tags in the tweet
  • 0.3% (22) only contained #xbio (last year’s hashtag)
  • 5.3% (359) used only #ASNatExpBio in the tweet

This confusion makes the use of these datasets for accurate analysis a little more difficult, and I likely missed some additional official and unofficial tags from separate societies. Of course if each society promotes its own hashtag this could lead to richer insights within each as well.

Network Graph

Here is a network graph showing the relationship of the most common words (several are twitter handles) in tweets and retweets that contained the hashtags. The connections between words are weighted in line size and color by how common they appear together in tweets.





*Tweets were collected using the Twitter Streaming API using a node.js app on Heroku. Analyses were done with Python and R, and the network graph in Gephi.

  • Jayme Crandall

    Waiting for your updated posts about artificial sweeteners in response to the new information. You left standing posts that pretend artificial sweeteners are not bad for you, convincing many that its totally healthy while they slowly developed diabetes and altered there entire gut microbiology, leading to their early death. Hopefully you can update your information regarding that so that people seeing your posts can then reference the new information. http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13793.html