Can your use of capitalization reveal your political affiliation?

This week, I’m in Vancouver this week for the meeting of the Association for Computational Linguistics. (On the subject of conferences, don’t forget that my offer to help linguistics students from underrepresented minorities with the cost of conferences still stands!) The work I’m presenting is on a new research direction I’m pursuing and I wanted to share it with y’all!

If you’ve read some of my other posts on sociolinguistics, you may remember that the one of its central ideas is that certain types of language usage pattern together with aspects of people’s social identities. In the US, for example, calling a group of people “yinz” is associated with being from Pittsburgh. Or in Spanish, replacing certain “s” sounds with “th” sounds is associated with being from northern or central Spain. When a particular linguistic form is associated with a specific part of someone’s social identity, we call that a “sociolinguistic variable”

There’s been a lot of work on the type of sociolinguistic variables people use when they’re speaking, but there’s been less work on what people do when they’re writing. And this does make a certain amount of sense: many sociolinguistic variables are either 1) something people aren’t aware they’re doing or 2) something that they’re aware they’re doing but might not consider “proper”. As a result, they tend not to show up in formal writing.

This is where the computational linguistics part comes in; people do a lot of informal writing on computers, especially on the internet. In fact, I’d wager that humans are producing more text now than at any other point in history, and a lot of it is produced in public places. That lets us look for sociolinguistics variables in writing in a way that wasn’t really possible before.

Which is a whole lot of background to be able to say: I’m looking at how punctuation and capitalization pattern with political affiliation on Twitter.

Political affiliation is something that other sociolinguists have definitely looked at. It’s also something that’s very, very noticeable on Twitter these days. This is actually a boon to this type of research. One of the hard things about doing research on Twitter is that you don’t always necessarily know someone’s social identity. And if you use a linguistic feature to try to figure out their identity when what you’re interested in is linguistic features, you quickly end up with the problem of circular logic.

Accounts which are politically active, however, will often explicitly state their political affiliation in their Twitter bio. And I used that information to get tweets from people I was very sure had a specific political affiliation.

For this project, I looked at people who use the hashtags #MAGA and #theResistance in their Twitter bios. The former is an initialism for “Make America Great Again” and is used by politically conservative folks who support President Trump. The latter is used by political liberal folks who are explicitly opposed to President Trump. These two groups not only have different political identities, but also are directly opposed to each other. This means there’s good reason to believe that they will use language in different ways that reflect that identity.

But what about the linguistic half of the equation? Punctuation and capitalization are especially interesting to me because they seem to be capturing some of the same information we might find in prosody or intonation in spoken language. Things like YELLING or…pausing….or… uncertainty?  They’re also much, much easier to measure punctuation than intonation, which is notoriously difficult and time-consuming to annotate.  At the same time, I have good evidence that how you use punctuation and capitalization has some social meaning. Check out this tweet, for example:

0b1022106daeb0d0419263dcf9c5aa93--this-is-me-posts

As this tweet shows, putting a capital letter at the beginning of a tweet is anything but “aloof and uninterested yet woke and humorous”.

So, if punctuation and capitalization are doing something socially, is part of what they’re doing expressing political affiliation?

That’s what I looked into. I grabbed up to 100 tweets each from accounts which used either #MAGA or #theResistance in their Twitter bios. Then I looked at how much punctuation and capitalization users from these two groups used in their tweets.

Punctuation

First, I looked at all punctuation marks. I did find that, on average, liberal users tended to use less punctuation. But when I took a closer look at the data, an interesting pattern emerged. In both the liberal and conservative groups, there were two clusters of users: those who used a lot of punctuation and those who used almost none.

punctuation

Politically liberal users on average tended to use less punctuation than politically conservative users, but in both groups there’s really two sets of users: those who use a lot of punctuation and those who use basically  none. There just happen to be more of the latter in #theResistance.

What gives rise to these two clusters? I honestly don’t know, but I do have a hypothesis. I think that there’s  probably a second social variable in this data that I wasn’t able to control for. It seems likely that the user’s age might have something to do with it, or their education level, or even whether they use thier Twitter account for professional or personal communication.

Capitalization

My intuition that there’s a second latent variable at work in this data is even stronger given the results for the amount of capitalization folks used. Conservative users tended to use more capitalization than the average liberal user, but there was a really strong bi-modal distribution for the liberal accounts.

Rplot

Again, we see that conservative accounts use more of the marker (in this case capitalization), but that there’s a strong bi-modal distribution in the liberal users’ data.

What’s more, the liberal accounts that used a lot of punctuation also tended to use a lot of capitalization. Since these features are both ones that I associate with very “proper” usage (things like always starting a tweet with a capital letter, and ending it with a period) this seems to suggest that some liberal accounts are very standardized in their use of language, while others reject at least some of those standards.

So what’s the answer the question I posed in the title? Can capitalization or punctuation reveal political affiliation? For now, I’m going to go with a solid “maybe”. Users who use very little capitalization and punctuation are more likely to be liberal… but so are users who use a lot of both. And, while I’m on the subject of caveats, keep in mind that I was only looking at very politically active accounts who discuss thier politics in their user bios.  These observations probably don’t apply to all Twitter accounts (and certainly not across different languages).

If you’re interested in reading more, you can check out the fancy-pants versions of this research here and here.  And I definitely intend to consider looking at this; I’ll keep y’all posted on my findings. For now, however, off to find me a Nanimo bar!

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Where 👏 do 👏 the 👏 claps 👏 go 👏 when 👏 you 👏 write 👏 like 👏 this 👏?

You may already be familiar with the phenomena I’m going to be talking about today: when someone punctuates some text with the clap emoji. It’s a pretty transparent gestural scoring and (for me) immediately brings to mind the way my mom would clap with every word when she was particularly exasperated with my sibling and I (it was usually along with speech like “let’s go, let’s go, let’s go” or “get up now”). It looks like so:

This innovation, which started on Black Twitter is really interesting to me because it ties in with my earlier work on emoji ordering. I want to know where emojis go, particularly in relation to other words. Especially since people have since extended this usage to other emoji, like the US Flag:

Logically, there are several different ways you can intersperse clap emojis with text:

  • Claps 👏  are 👏 used 👏 between 👏 every 👏 word.
  •  👏 Claps 👏 are 👏 used 👏 around 👏 every 👏 word. 👏
  •  👏 Claps 👏 are 👏 used 👏 before 👏 every 👏 word.
  • Claps 👏 are 👏 used 👏 after 👏 every 👏 word. 👏
  • Claps 👏 are used 👏 between phrases 👏 not words

I want to know which of these best describes what people actually do. I’m not aiming to write an internet style guide, but I am hoping to characterize this phenomena in a general way: this is how most people who do this do it, and if you want to use this style in a natural way, you should probably do it the same way.

Data

I used Fireant to grab 10,000 tweets from the Twitter streaming API which had the clap emoji in them at least once. (Twitter doesn’t let you search for a certain number of matches of the same string. If you search for “blob” and “blob blob” you’ll get the same set of results.)

Analysis

From that set of 10,000 tweets, I took only the tweets that had a clap emoji followed by a word followed by another clap emoji and threw out any repeats. That left me with 260 tweets. (This may seem pretty small compared to my starting dataset, but there were a lot of retweets in there, and I didn’t want to count anything twice.) Then I removed @usernames, since those show up in the beginning of any tweet that’s a reply to someone, and URL’s, which I don’t really think of as “words”. Finally, I looked at each word in a tweet and marked whether it was a clap or not. You can see the results of that here:

timecourse

The “word” axis represents which word in the tweet we’re looking at: the first, second, third, etc. The red portion of the bar are the words that are the clap emoji. The yellow portion is the words that aren’t. (BTW, big shoutout to Hadley Wickham’s emo(ji) package for letting me include emoji in plots!)

From this we can see a clear pattern: almost no one starts a tweet with an emoji, but most people follow the first word with an emoji. The up-down-up-down pattern means that people are alternating the clap emoji with one word. So if we look back at our hypotheses about how emoji are used, we can see right off the bat that three of them are wrong:

  • Claps 👏  are 👏 used 👏 between 👏 every 👏 word.
  •  👏 Claps 👏 are 👏 used 👏 around 👏 every 👏 word. 👏
  •  👏 Claps 👏 are 👏 used 👏 before 👏 every 👏 word.
  • Claps 👏 are 👏 used 👏 after 👏 every 👏 word. 👏
  • Claps 👏 are used 👏 between phrases 👏 not words

We can pick between the two remaining hypotheses by looking at whether people are ending thier tweets with a clap emoji. As it turns out, the answer is “yes”, more often than not.

endWithClap

If they’re using this clapping-between-words pattern (sometimes called the “ratchet clap“) people are statistically more likely to end their tweet with a clap emoji than with a different word or non-clap emoji. This means the most common pattern is to use 👏 a 👏 clap 👏 after 👏 every 👏 word, 👏  including  👏 the  👏 last. 👏

This makes intuitive sense to me. This pattern is mimicking someone is clapping on every word. Since we can’t put emoji on top of words to indicate that they’re happening at the same time, putting them after makes good intuitive sense. In some sense, each emoji is “attached” to the word that comes before it in a similar way to how “quickly” is “attached” to “run” in the phrase “run quickly”. It makes less sense to put emoji between words, becuase then you end up with less claps than words, which doesn’t line up well with the way this is done in speech.

The “clap after every word” pattern is also what this website that automatically puts claps in your tweets does, so I’m pretty positive this is a good characterization of community norms.

 

So there you have it! If you’re going to put clap emoji in your tweets, you should probably do 👏 it 👏 like 👏 this. 👏 It’s not wrong if you don’t, but it does look kind of weird.

What’s up with calling a woman “a female”? A look at the parts of speech of “male” and “female” on Twitter .

This is something I’ve written about before, but I’ve recently had several discussions with people who say they don’t find it odd to refer to a women as a female. Personally, I don’t like being called “a female” becuase its a term I to associate strongly with talking about animals. (Plus, it makes you sound like a Ferengi.)  I would also protest men being called males, for the same reason, but my intuition is that that doesn’t happen as often. I’m willing to admit that my intuition may be wrong in this case, though, so I’ve decided to take a more data-driven approach. I had two main questions:

  • Do “male” and “female” get used as nouns at different rates?
  • Does one of these terms get used more often?

Data collection

I used the Twitter public API to collect two thousand English tweets, one thousand each containing the exact string “a male” and “a female”. I looked for these strings to help get as many tweets as possible with “male” or “female” used as a noun. “A” is what linguist call a determiner, and a determiner has to have a noun after it. It doesn’t have to be the very next word, though; you can get an adjective first, like so:

  • A female mathematician proved the theorm.
  • A female proved the theorm.

So this will let me directly compare these words in a situation where we should only be able to see a limited number of possible parts of speech & see if they differ from each other. Rather than tagging two thousand tweets by hand, I used a Twitter specific part-of-speech tagger to tag each set of tweets.

A part of speech tagger is a tool that guesses the part of speech of every word in a text. So if you tag a sentence like “Apples are tasty”, you should get back that “apples” is a plural noun, “are” is a verb and “tasty” is an adjective. You can try one out for yourself on-line here.

Parts of Speech

In line with my predictions, every instance of “male” or “female” was tagged as either a noun, an adjective or a hashtag. (I went through and looked at the hashtags and they were all porn bots. #gross #hazardsOfTwitterData)

However, not every noun was tagged as the same type of noun. I saw three types of tags in my data: NN (regular old noun), NNS (plural noun) and, unexpectedly, NNP (proper noun, singular). (If you’re confused by the weird upper case abbreviations, they’re the tags used in the Penn Treebank, and you can see the full list here.) In case it’s been a while since you studied parts of speech, proper nouns are things like personal or place names. The stuff that tend to get capitalized in English. The examples from the Penn Treebank documentation include “Motown”, “Venneboerger”,  and “Czestochwa”. I wouldn’t consider either “female” or “male” a name, so it’s super weird that they’re getting tagged as proper nouns. What’s even weirder? It’s pretty much only “male” that’s getting tagged as a proper noun, as you can see below:

maleVsFemalePOS

Number of times each word tagged as each part of speech by the GATE Twitter part-of-speech tagger. NNS is a plural noun, NNP a proper noun, NN a noun and JJ an adjective.

The differences in tagged POS between “male” and “female” was super robust(X2(6, N = 2033) = 1019.2, p <.01.). So what’s happening here?  My first thought was that it might be that, for some reason, “male” is getting capitalized more often and that was confusing the tagger. But when I looked into, there wasn’t a strong difference between the capitalization of “male” and “female”: both were capitalized about 3% of the time. 

My second thought was that it was a weirdness showing up becuase I used a tagger designed for Twitter data. Twitter is notoriously “messy” (in the sense that it can be hard for computers to deal with) so it wouldn’t be surprising if tagging “male” as a proper noun is the result of the tagger being trained on Twitter data. So, to check that, I re-tagged the same data using the Stanford POS tagger. And, sure enough, the weird thing where “male” is overwhelming tagged as a proper noun disappeared.

stanfordTaggerPOS

Number of times each word tagged as each part of speech by the Stanford POS tagger. NNS is a plural noun, NNP a proper noun, NN a noun, JJ an adjective and FW a “foreign word”.

So it looks like “male” being tagged as a proper noun is an artifact of the tagger being trained on Twitter data, and once we use a tagger trained on a different set of texts (in this case the Wall Street Journal) there wasn’t a strong difference in what POS “male” and “female” were tagged as.

Rate of Use

That said, there was a strong difference between “a female” and “a male”: how often they get used. In order to get one thousand tweets with the exact string “a female”, Twitter had to go back an hour and thirty-four minutes. In order to get a thousand tweets with “a male”, however, Twitter had to go back two hours and fifty eight minutes. Based on this sample, “a female” gets said almost twice as often as “a male”.

So what’s the deal?

  • Do “male” and “female” get used as nouns at different rates?  It depends on what tagger you use! In all seriousness, though, I’m not prepared to claim this based on the dataset I’ve collected.
  • Does one of these terms get used more often? Yes! Based on my sample, Twitter users use “a female” about twice as often as “a male”.

I think the greater rate of use of “a female” that points to the possibility of an interesting underlying difference in how “male” and “female” are used, one that calls for a closer qualitative analysis. Does one term get used to describe animals more often than the other? What sort of topics are people talking about when they say “a male” and “a female”? These questions, however, will have to wait for the next blog post!

In the meantime, I’m interested in getting more opinions on this. How do you feel about using “a male” and “a female” as nouns to talk about humans? Do they sound OK or strike you as odd?

My code and is available on my GitHub.