No network analysis today!
Today we'll focus on the content and how science is (almost) taking over the not-scientific content!
We classified the tweets (scientific Vs not-scientific) across 3 time points: pre-conference, day1 and day2
The proportion of scientific tweets increased on day2 (from 30% to 40%) ... a big jump!
Then we analyzed in more detail the 'scientific' tweets. Two categories were formed: Original (tweets without RT tag) and RT (tweets containing the RT tag). We assume that tweets without the RT contain original content, while RT tweets play the role of "redundant" signal (repetition code).
Content originality jumped up as the meeting started on day 1 and remained stable on day2.
Social issues, social issues.. Sex differences.. Not a surprise that a 'social' talk got A LOT of attention in a social medium like Twitter...
Too bad that we had no categories for classifying "Social Neuroscience"!!!! So our algorithm decided to cluster all of Cahill-related tweets in the Neuroendocrine category!
That's the place were you would place tweets containing a word like 'sex', right? ... or maybe Sensory and Motor Disorders? Development? ... Maybe Cellular Cechanisms: optogenetics is soooo 'sexy' nowadays.....