The X axis label there is tricky, and tripped me up for a bit -- although they look like they could be percentages, they actually aren't -- they're "# of uses of term per million words of text". So the fraction of evaluations that actually use the term is actually pretty small.
This might be cheering news to people concerned that their students haven't been referring to them as "geniuses" on their evaluations. Although, actually, as a Math PhD, my instinct is that if a student is using the word "genius", it's probably a negative evaluation (of the "I'm sure she's a genius, but she can't teach" type -- although "you have to be a genius to take the class" is another possibility). And indeed -- math is the field where the word "genius" is most often used in negative reviews, and for women in math, the word "genius" is used twice as often in negative reviews as in positive reviews. (For men, the difference is smaller, but the word "genius" is still seen more often in negative reviews.)
Anyway, it's a really nifty tool (Ben Schmidt does a lot of awesome visualization!) I do wish it had error bars -- for less common words (e.g. "penguin"), the differences are probably mostly noise, though I'm totally willing to believe that CS is the field with the most penguins!
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Date: 2015-02-08 02:31 am (UTC)This might be cheering news to people concerned that their students haven't been referring to them as "geniuses" on their evaluations. Although, actually, as a Math PhD, my instinct is that if a student is using the word "genius", it's probably a negative evaluation (of the "I'm sure she's a genius, but she can't teach" type -- although "you have to be a genius to take the class" is another possibility). And indeed -- math is the field where the word "genius" is most often used in negative reviews, and for women in math, the word "genius" is used twice as often in negative reviews as in positive reviews. (For men, the difference is smaller, but the word "genius" is still seen more often in negative reviews.)
Anyway, it's a really nifty tool (Ben Schmidt does a lot of awesome visualization!) I do wish it had error bars -- for less common words (e.g. "penguin"), the differences are probably mostly noise, though I'm totally willing to believe that CS is the field with the most penguins!