Number of articles grows exponentially (doubling time: 15 years), while number of "ideas" (measured by examining unique phrases in title) grows linearly.pic.twitter.com/v8YIXDIIRq
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Number of articles grows exponentially (doubling time: 15 years), while number of "ideas" (measured by examining unique phrases in title) grows linearly.pic.twitter.com/v8YIXDIIRq
Apparently there is evidence that interdisciplinary work is viewed as more valuable after the fact, but less valuable before. (cc @davidmanheim, evidence supporting your tweets earlier)pic.twitter.com/BT7Cg8Pw35
This looks like a boring graph, but in fact it's the regularity which is interesting: it's the histogram of occurrences of highest-impact paper in a scientist's sequence of publications. The punchline is that it's equally likely at any time in their career.pic.twitter.com/S8xYzeUurn
This contradicts some cynical remarks I've occasionally heard - that people at higher-status institutions get treated unfairly well. At least in terms of the impact of their papers, that appears to be false. (It may be true in other ways, of course).pic.twitter.com/S92PBk6TYs
There's a lot of work supporting this, what Simonton calls the "equal odds" rule: the l'hood of a paper being important is roughly constant across a career (&, according to S, across scientists). Much as people hate it, & there are anecdotal counter-egs, # of pubs often matterspic.twitter.com/uhuoafb8hD
The size of teams has increased over time. Black curves are for higher-impact papers, red curves for all papers.pic.twitter.com/tHXHnyI8Tj
"A team-authored paper in science and engineering is 6.3 times more likely to receive 1000 or more citations..."pic.twitter.com/3q0Ph9SADD
Interrupting this tweet stream to mention: it is _of course_ true that citations != quality of a paper. Not even close. Keep that in mind for all these facts! But the facts are still food for thought, IMO.
This - diversity in team size (& everything else, frankly) - I thoroughly endorse. I'm all for chaotically trying everything...pic.twitter.com/RehKxNL30z
Teams are growing, an average, 17% per decade. That's really not all that fast. It means a doubling time of about 44 years.
Something I do wonder about in connection with the equal odds rule across a scientists' career: does it take into account the fact that in many fields citation rates are (I believe) rising? If so, the numbers should be rescaled.
The probability density for a paper's number of citations, normalized by the average number of citations for its discipline. The is essentially identical across disciplines(!) This is honestly quite remarkable.pic.twitter.com/SQvHcmabee
It's striking how much the paper focuses on citations and similar measures, but not on things like understanding, quality of explanations, deep new ideas, and so on; nor on economic impacts. Lots of proxy measures, rather than the reasons we want to do science in the first place
Put another way, it's not so much about the science of science, as the science of the extremely limited set of things we can measure about science. Citations are not uninteresting, but there's a reason Boltzmann's grave has S = k log W on it, not his h-indexpic.twitter.com/RVhOGtTaEA
Anyways, it's a useful survey paper, with much that was new to me in it. And it was fun to make a first pass over it "in public" like this 
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