Experimental Biology 2014 Tweet Analysis #xbio

Like last year, I collected all tweets posted to #xbio and #eb2014 over the Experimental Biology conference. Here they are in a CSV file. Last year there were 5,455 over a 10 day period, and this year there are 6,223 over an 18 day period. During the last 8 days there were only about 120 tweets, so there were about 600 more tweets this year, and that was with a technology fail and loss of about 20 hours of tweets on the 30th (see graph). So there were probably at least several hundred more in that period. Also like last year, I captured photos posted to the hashtag and uploaded them to this tumblr so they are all in one place. Below are some additional comparisons*:

Tweet Frequency Over the Conference

This year reached a higher peak tweet frequency compared to last year:

plot_zoom_png Rplot

Tweets Per Person and Number of Tweeters

There was a lower average number of tweets per person this year, but more people tweeted to the hashtags.

2014

2013

Average SD Average SD
4.9 14.5 6.3 21

The median for both years was 1 tweet.

2014

2013

Number of Tweeters

Number of Tweeters

1,278 864

Top 10 Tweeters

2014

2013

Handle Tweet Count Handle Tweet Count
ASBMB 226 Biochembelle 292
Biochembelle 196 Drdairy50 243
Daviddespain 190 ASBMB 223
Drugmonkeyblog 159 Daviddespain 211
Expbio 112 Bwcorb 185
cjmetzgarRD 104 LICORBio 122
Nutritionorg 88 DrAmyRD 116
Drdairy50 81 Nutritionorg 92
PHLane 77 ChrisPickett5 81
Paulaike 74 Phyziochick 81

Top 10 Tweets 2014 (+ Retweeted Count)

Tweet Retweeted Count
RT @daviddespain: John Jakicic: “Please consult with your physician if you decide NOT to engage in regular daily #physicalactivity “ 38
RT @SamFlatow: That groggy morning feeling is “sleep inertia”. Lets you fall back asleep after waking at night. Normally goes away after 15… 26
RT @SCRDinDC: Love this.. “Never be afraid to admit you’re wrong because it shows you’re smarter today than you were yesterday” – Dr. Bier … 22
RT @FizzyDoc: Why do YOU research?! #nerdhumor #eb2014 #cooltshirt t.co/Z1l2488hsM 19
RT @SamFlatow: 3d printed therapeutic skull fragments are now science, not fiction #xBio 19
RT @daviddespain: Stop singling out sugar t.co/T47Nk1LKxn my post about today’s sugar session @nutritionorg #XBio #sugarshowdown 17
RT @daviddespain: Are you really addicted to food? (spoiler: probably not) t.co/QnkxO4qfoL my post from #XBio @nutritionorg @ILSI_NA… 15
RT @SCRDinDC: “Dietary patterns (not single nutrients) have the greatest impact on weight gain and cardiometabolic risk.” – Dr. Sievenpiper… 15
RT @daviddespain: Sievenpiper says misguided views on sugar from Lustig are “becoming doctrine”, reaching mainstream #xbio #sugarshowdown 13
RT @Rednuria: B. Stillman: Every minute, your bone marrow copies accurately 1 million Km worth of DNA… BOOM!! #xBio #science 13

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 by how common they appear together in tweets. netgraph

Locations

These are maps of the home locations of each person who tweeted to the hashtags and who included their home locations in their profile. It is a similar pattern to last year: map2014EB2013 Most are from the US, but some are all over the world (click to enlarge): world

Hashtag Confusion?

This year, the hashtag was switched to #xbio instead of of #eb2014 (last year was #eb2013). I looked to see if people adopted the new one. Most appeared to get the message:

  • 83% of tweets contained only the #xbio hashtag
  • 12% contained only the #eb2014 hashtag
  • 5% contained both hashtags

 

Have any additional analysis requests? Post them in the comments!

 

 

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