The whimsical world of emoji swearing

This is a guest post by Dr Philip Seargeant, Senior Lecturer in Applied Linguistics at the Open University. Philip has published extensively on topics such as language and social media, English around the world, and language and creativity. With his colleagues he produced the acclaimed video series The History of English in Ten Minutes. He tweets at @philipseargeant.

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How do you say ‘cockwomble’ in emoji?

Is it possible to swear in emoji? According to BuzzFeed, the answer’s a definite yes. In what has all the elements of an archetypal BuzzFeed post, the site provides a handy run-down of twenty-one useful emoji expletives. This includes staples such as ‘bastard’ 👪🚫💍 and ‘wanker’ 👐⚓️. Then there are the slightly more esoteric terms like ‘cockwomble’ 🐓🐹, which led the vanguard in the Scottish anti-Trump protests last summer. And finally there are a few useful compounds such as ‘bollock-faced shit licker’ 🍒😃💩👅.

While emoji may have started life as a way of adding fairly straightforward emotion-related context to a message – a smiling face at the end of a sentence to indicate that you’re joking, etc. – as their popularity has grown, so has the range of functions for which they’re used. Nowadays they can be employed for everything from expressing political allegiances, to conveying threats and combating cyberbullying.

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7½ minutes of Sean Bean swearing

We’ve featured swearing montages from video games; now here’s one from TV.

Even if you’ve never seen Sharpe (I haven’t), that won’t stop you enjoying Sean Bean uttering oaths from it non-stop for 7½ minutes – mostly bastard, bloody, bugger and damn, with crap, arse, piss, prick and twat entering the fray near the end and culminating in this mighty outburst:

What an idiot. What a dirty little Dutch buffle-brained bastard. I’ll ram his poxed crown up his royal poxed arse. The blue-blooded twat.

Sean Bean Sharpe two fingers gesture

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New voice transcription feature in Google Docs censors (some!) swearwords

Google Docs announced today that you can now create documents using your voice.  And of course, like any good linguist, I immediately went to try to stump it. It’s pretty good, actually — it recognized both pronunciations of “gif” and “aunt” in the contexts “animated ___” and “uncle and ___” although it tended to assume that I might have the bit/bet merger, which I most emphatically do not, and thus presented me with a few transcriptions that felt like odd candidates to me.

But then I tried swearwords and hit the fucking jackpot. Continue reading

Unparliamentary language: Australian edition

1024px-Australian_parliament_inside

Legislators in governments based on the Westminster system enjoy parliamentary privilege, which means that, while in the House, they can speak their minds without the fear of being sued for slander. But to retain some modicum of decorum during debates, the Speaker of the House has the authority to rein in politicians who use language deemed unparliamentary, asking foul-mouthed lawmakers to withdraw their comments or face discipline.

This post is the first of a series that takes you on a tour of unparliamentary language in the Commonwealth. Some examples are insults thrown about by Australia’s “honourable members,” most of which are relatively tame by Strong Language standards, whereas others are a bit more meta, coming from legislative discussions about unseemly language itself. (The lack of quotes from certain states is more an indication of hard-to-search Hansards rather than a high standard of politeness.) Continue reading

Mapping the United Swears of America

Swearing varies a lot from place to place, even within the same country, in the same language. But how do we know who swears what, where, in the big picture? We turn to data – damn big data. With great computing power comes great cartography.

Jack Grieve, lecturer in forensic linguistics at Aston University in Birmingham, UK, has created a detailed set of maps of the US showing strong regional patterns of swearing preferences. The maps are based on an 8.9-billion-word corpus of geo-coded tweets collected by Diansheng Guo in 2013–14 and funded by Digging into Data. Here’s fuck:

Jack Grieve swear map of USA GI z-score FUCK Continue reading