Twitter's new favourite words

[Jonathan Lighter]

Did you try "most favorite word"?

JL


On Fri, Oct 25, 2013 at 5:54 AM, Hugo <hugovk at gmail.com> wrote:

> ---------------------- Information from the mail header
> -----------------------
> Sender:       American Dialect Society <ADS-L at LISTSERV.UGA.EDU>
> Poster:       Hugo <hugovk at GMAIL.COM>
> Subject:      Twitter's new favourite words
>
> -------------------------------------------------------------------------------
>
> I wrote a Python script that searches Twitter for tweets containing "[X]
> is my new favourite word". It then takes all those new favourite words,
> logs them, lowercases them, and adds them to a list of words on Wordnik.
> And, from this week, it also tweets them and makes word clouds.
>
> It also does the same for "[X] is my new favorite word" and "[X] is my new
> fave word" so you can see some geographic variation.
>
> It's been going six months since 24th February 2013, runs nearly every
> day, and has found some 18,360 new favourite words.
>
> Here's top tens for the whole set and each subset.
>
> The whole data set contains 18,360 words and 10,018 unique words.
> The top 10 words are:
> 1. no (151)
> 2. cunt (120)
> 3. sassy (99)
> 4. bitch (95)
> 5. ratchet (87)
> 6. fab (86)
> 7. twat (73)
> 8. cheeky (72)
> 9. faggot (66)
> 10. fuck (62)
>
> "New favorite words" contains 10,299 words and 5,964 unique words.
> The top 10 words are:
> 1. no (129)
> 2. cunt (75)
> 3. bitch (73)
> 4. ratchet (55)
> 5. thot (53)
> 6. fuck (47)
> 7. twat (41)
> 8. sassy (38)
> 9. fuckery (36)
> 10. whatever (35)
>
> "New favourite words" contains 6,623 words and 4,505 unique words.
> The top 10 words are:
> 1. fab (50)
> 2. sassy (50)
> 3. cunt (41)
> 4. cretin (36)
> 5. cheeky (34)
> 6. faggot (33)
> 7. fabulous (32)
> 8. twat (29)
> 9. ratchet (24)
> 10. serendipity (20)
>
> "New fave words" contains 1,436 words and 1,162 unique words.
> The top 10 words are:
> 1. fab (19)
> 2. sassy (11)
> 3. ratchet (8)
> 4. cheeky (7)
> 5. swaggot (7)
> 6. cretin (7)
> 7. coont (6)
> 8. bastard (6)
> 9. dope (6)
> 10. dude (5)
>
> What does this tell us? I don't know, but whilst the top ten contains lots
> of swearing, around half (or about 2/3 for favourites) of each list
> contains unique words. Browsing the lists shows lots of neologisms (and
> neoswearisms).
>
> The word lists on Wordnik:
> http://www.wordnik.com/lists/twitter-favourites
> http://www.wordnik.com/lists/twitter-favorites
> http://www.wordnik.com/lists/twitter-faves
>
> Follow along:
> https://twitter.com/favibot
>
> See word clouds:
> http://www.flickr.com/photos/hugovk/sets/72157636928894765/
>
> See the script:
> https://github.com/hugovk/word-tools/blob/master/new_favourite_words.py
>
> Inspired by:
> http://www.wordnik.com/lists/outcasts
>
> Hugo
>
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> The American Dialect Society - http://www.americandialect.org
>



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