It got me thinking: I know these aren't good backronyms, but what is it that makes a good one? I think a noun stack would work. I also think some combination of adjectives followed by a noun works. If we apply a Madlib-esque approach to the generator, we should be able to get passable backronyms. I'll try to make something that can do this and post more later.
5 hours ago
9 comments:
I've been thinking about this and I think one of the best ways to do it would be to take a list of existing acronyms (especially bureaucratic ones) and weight the generator so that it tends to use the words from the list more often. For example, this would mean "International" would come up much much more often for "I" than "Igloo."
Sort of how Google's translation stuff works; just take a corpus of good samples and use it and you come out looking much smarter (although occasionally dumb but in this case dumb would be funny and good).
Definitely an interesting approach. It looks like acronymfinder won't give up their list of 4 million acronyms for free (not that they are necessarily a good list, just numerous), but I see that wikipedia has a list that is ripe for the scraping. Maybe there are others...
http://www.lib.umich.edu/govdocs/fedexec.html#acronyms
http://ucblibraries.colorado.edu/govpubs/a-z/alpha.htm
Thanks for the links Tim!
Kevin, I am doing some Stimulus package research for a Consultant. I am interested in leveraging the work you did in StimulusWatch.Org as part of a State (s) recovery site. This consultant has already done some work for DC. How can I find out more about the Project ratings?? Is it some formula around the % of Critical votes vs. Non Critical, # of votes, and jobs created? This would be helpful to know. Thanks, Miles
Miles, it's just this formula: positive_votes - negative_votes
So it's not a normal ratio, it's more of a measure of the balance between positive and negative. One side-effect of this method is that a project with 1000 positives and 1000 negatives sorts to the same place as one with 1 positive and 1 negative. I think that's what you want, but it's something to consider nevertheless.
Look at you with all your parts of speech. Maybe you should come to my school and explain to all my little darlings that even computer people need to know what adjectives are.
Have you gotten anywhere with this. A program we can try out?
One thought I had is once the words are generated, an option to permanently eliminate particular words.........z
You'll have to excuse the SSL certificate chicanery, but yes there is a working demo here: https://labs.pheared.net/construct/backronym
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