Tears of Joy for Word of the Year

Face with tears of joyThe era of a new language has truly arrived. This year, Oxford Dictionaries has named an emoji as its word of the year.

It’s a bold choice, but a rock-solid one linguistically. No single word has dominated 2015, as Collins’ recent choice of binge-watch for their word the year vividly demonstrates. Instead we are at the dawn of a new way of communicating, and the Oxford choice confirms this.

The trend has been obvious for the last 12 months. The Global Language Monitor started the ball rolling by picking an emoji as its word of 2014. Then earier this year, a linguist described emoji as the fastest evolving language of all time. And so this decision will catapult recognition of that growth into the mainstream.

Casper Grathwohl, President of Oxford Dictionaries, said: “You can see how traditional alphabet scripts have been struggling to meet the rapid-fire, visually focused demands of 21st Century communication. It’s not surprising that a pictographic script like emoji has stepped in to fill those gaps—it’s flexible, immediate, and infuses tone beautifully. As a result emoji are becoming an increasingly rich form of communication, one that transcends linguistic borders.” Amen to all of that.

For the record, the emoji which accepts the accolade on behalf of all its emoji brethren is 😂 –  ‘Face with tears of joy’.  According to mobile technology company Swiftkey, which partnered with Oxford to help decide on the winner, ‘Face with Tears of Joy’ was the most heavily used emoji globally in 2015. It comprised 20% of all emoji used in the UK in 2015, and 17% of all emoji used in the US.

This announcement will be greeted by criticism from some, derision from others. People will complain that it is not a word, will lament what is happening to our language, will somehow feel that Oxford Dictionaries itself is no longer the great arbiter it once was because it is making this decision. All utter nonsense, of course.

Instead, everyone should recognise that language is changing at a pace never before known, that a new lingua franca is emerging for the global, connected era in which we live, and that if hieroglyphs were good enough for the civilised ancient Egyptians, then using images to communicate with others should still be acceptable today. My linguistic tears of joy for this decision are all real.

Other shortlisted words:

ad blocker, noun:
A piece of software designed to prevent advertisements from appearing on a web page.

Brexit, noun:
A term for the potential or hypothetical departure of the United Kingdom from the European Union.

Dark Web, noun:
The part of the World Wide Web that is only accessible by means of special software, allowing users and website operators to remain anonymous or untraceable

lumbersexual, noun:
a young urban man who cultivates an appearance and style of dress (typified by a beard and checked shirt) suggestive of a rugged outdoor lifestyle

on fleek, adjective (usually in phrase on fleek):
extremely good, attractive, or stylish

refugee, noun:
A person who has been forced to leave their country in order to escape war, persecution, or natural disaster.

sharing economy, noun:
An economic system in which assets or services are shared between private individuals, either free or for a fee, typically by means of the Internet.

they (singular), pronoun:
Used to refer to a person of unspecified sex.

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The Swiftkey Way To Learning New Words

The number of new words contributed to the English language by technology is well known. But how does a company which provides technology to help with language and communication cope with the ever-expanding tide of vocabulary?

Swiftkey
Swiftkey in action

Swiftkey has garnered praise and awards for its predictive text app. Its nifty software allows users of Android devices to speed up their typing by anticipating what they are going to type and then suggesting it for them.

I wondered how the Swiftkey database keeps up to date, to ensure that it can offer users the newest words on the block. So I asked Dr Caroline Gasperin, who leads a team of eight language processing engineers responsible for most language-related tasks at the London-based company.

She explained that Swiftkey learns an individual’s linguistic habits, and that by extension this grows its global database as a result.

“Your SwiftKey will learn any word you teach it, you only have to type it once and it will be included in your personal language model on your device,” she said.

“Through the Personalisation feature – which allows you to sync it with your Gmail, Facebook and Twitter accounts – and through continuous use, SwiftKey learns the words you use and the contexts in which you use them so that its predictions and corrections are based on your own way of writing.”

This learning can then feed into the overall word database to help the word corpus grow. Caroline said: “We’ve started putting in place the infrastructure for learning new words from our user base.

“As users use the Personalisation feature of SwiftKey, we are able to collect statistics about the words they use and identify words that we did not know before. We are putting in place a semi-automatic process to identify which of those words could become part of a standard dictionary and consequently become part of our downloadable language modules.

“This process consists of observing the frequency of use of words over time: words which used to have few occurrences across our user base, but which start becoming more frequent over time, and which are mentioned by several of our users instead of by just one or a few, are considered as good candidates for being added to our dictionaries.

“It’s worth adding we take our users’ privacy extremely seriously and have policies in place to safeguard this. We do not process a user’s data personally.”

Dr Caroline Gasperin
Dr Caroline Gasperin

So has the way that new words are assimilated changed, and is the process quicker than before? Caroline said: “We look into how many different people have used an unknown word in order to consider it as a potential new word in the language instead of a personal word.

“We take our users’ privacy seriously, so we’ve developed ways to discover words in wide use instead of focusing on single users.

“We haven’t followed users’ language use for long enough to know whether new words are being adopted faster than before, but we are working on getting those statistics.”

I have long since believed that new words are being created and accepted into the language considerably quicker than before, with technology the principal driver behind that evolution. It would be interesting to revisit Swiftkey at some point soon to see whether those promised statistics back up that theory. And the company also gives us a very clear steer about how its core business has to adapt to the ever-changing delights of the English language.