AUTUMNAL UPDATES

The Autumn Equinox, and time for the latest perspectives on slang and youth language in the Anglosphere…

I‘m very grateful indeed for the latest data on the most popular slang terms – according to online searches – among younger people in the USA, provided once again by Randoh Sallihall of Unscramblerer.com

Most searched for slang words in America:

1.      6-7 (141 000 searches) – There is no literal meaning to six seven. Its absurdity is the point, making it a prime example of “brainrot” internet humor where the randomness itself becomes funny. It originates from the song “Doot Doot (6 7)” by Skrilla. LaMelo Ball a basketball player created a trending video about being 6 feet 7 inches tall using the song. Kids and teens scream and chant it often paired with exaggerated hand gestures. *See also below

2.      Bop (115 000 searches) – A person with many sexual partners (bops around from person to person). Someone who presents oneself online in a way that is thought of as immodest. A derogatory word often used in cyberbullying.

3.      Mogging (79 000 searches) – outclassing someone else by appearing more attractive, skillful or successful. Looksmaxxing (16 000 searches)  has a similar meaning that is also a trending slang word this year.

4.      Huzz (61 000 searches) – refers to attractive girl or a group of girls. A replacement for ‘boo’ and ‘pookie’. Somebody you want to impress. This slang had a more derogatory meaning ‘h–s’, but that has changed.

5.      Chopped (59 000 searches) – this term has become a synonym for something that is ugly, undesirable or unattractive.

6.      Big back (57 000 searches) – refers to someone with a large physique. Someone who is seen as gluttonous or out of shape. It’s less about literal size and more about poking fun at behavior, like hogging food or being sluggish.

7.      Glazing (49 000 searches) – means to praise someone excessively and insincerely. A way to call out behavior where excessive flattery is used.

8.      Zesty (44 000 searches) – someone who is lively, exciting or energetic.

9.      Fanum tax (36 000 searches) – playfully taking a portion of a friend’s food. The streamer Fanum began this trend.

10.   Green FN (34 000 searches) – refers to a guaranteed win. Describes something amazing and highly desirable. Often said after an exceptional shot or throw in basketball. The term originates from the NBA 2K video game series, where a perfectly timed shot is marked by the color green.

11.   Delulu (32 000 searches) – short for delusional. It describes someone with unrealistic expectations, especially about crushes, relationships, or fantasies (thinking a celebrity will date them).

12.   Clanker (29 000 searches) – is a derogatory term for robots and AI technology. An example would be “having to talk to a clanker” would mean talking with a chat bot.

13.   Ohio (24 000 searches) – refers to anything that is strange or absurd.

14.   Slop (21 000 searches) – describes low effort AI generated content.

15.   Aura farming (18 000 searches) -refers to a behavior (often referencing anime characters) where a person does something for the sake of looking cool.

A spokesperson for Unscramblerer.com commented on the findings: “Popular slang in 2025 continues to be heavily influenced by TikTok, Instagram, gaming, streaming, Gen Z and Alpha online communities. Trends from social media spread rapidly via memes and viral challenges. Fueled by technology our language adapts to new slang trends more rapidly than ever. Slang is a fascinating and fun mirror of our culture.”

Research was conducted by word finding experts at Unscramblerer.com.

We analyzed 01.01.2025 -19.09.2025 search data from Google Trends for terms related to slang words.

Methodology: We used Google Trends to discover the top trending slang terms and Ahrefs to find the number of searches. Americas most popular slang terms can be discovered in Google Trends through the keyword ‘meaning’. People will hear or read slang terms and search for the meaning of the term (example ‘mogging meaning’). Ahrefs shows many variations of meaning searches like ‘slang’ or ‘trend’ (example ‘mogging slang’) and similar keyword combinations (example ‘ what does demure mean’). We added up 150 search variations of top slang terms.

The words recorded in the US can be compared with this list of slang collected in UK schools by Teacher Tapp in August…

https://teachertapp.com/uk/articles/down-with-the-kids-slang-in-british-classrooms-2025/

Earlier this month I spoke to Avantika Bhuyan, Editor at India’s Mint Lounge magazine, about the youngest online cohort, Gen Alpha. She asked me how their interactions with technology and language differed from their predecessors…

Gen Alpha are of course the first generational cohort to have grown up wholly surrounded by digital technology, digital media and the online culture that accompanies them. They are adept at using the hardware – mobile phones, tablets, gaming gadgets – but also unlikely to be dazzled by these already dated mechanical devices. They have sometimes returned to old fashioned film cameras and Polaroids, wind-up watches, puzzles and pinballs as interesting relics (something which in older users is described by theorists as ‘haptic nostalgia’. For them AI isn’t a terrifying threat but just part of the digital landscape they navigate daily.

Gen Alpha are active on YouTube (short-form video by preference), Instagram and – especially – TikTok where they can participate and emulate, or react to influencers and content-creators and individual TikTok celebrities, This media reinforces accelerated performances, exaggerated poses and a pervading sense of self-consciousness, self-mockery, irony and absurdist humour, prompted partly by their collective anxiety at being on display, surveilled and judged 24/7.

Gen Alpha slang, like GenZ’s differs from that of older generations in that it’s not just language that arises ‘naturally’, escaping from the streets or disseminated by movies, TV and the music industry. The language they use has often been generated deliberately by techbros, influencers and microcelebrities who are not just trying to communicate but to gain prestige, kudos. The slang they use also differs from older versions in ways which are interesting to linguists like me: the ‘words’ are not just words but operate virally like memes and, like memes, they are ‘multimodal’, made up not just of writing or sounds like traditional words but accompanied by images, sound effects, references to other messages, in-jokes, puns, etc.

Older generations often find Gen Alpha’s vocabulary baffling, ridiculous or annoying – unsurprisingly since the language is used in part to project behaviour and values that are alien to parents, teachers. Key words – such as ‘skibidi’ – may actually be meaningless, more comic gestures than information-bearers and the passing visual fads and fashions that Gen Alpha (and Gen Z) indulge in – microtrends and looks and what they call ‘aesthetics’ or ‘vibes’- are not designed to last.

There may be serious effects to these innovations and new behaviours. Dating is much more fraught, more competitive when its potentially being exposed globally, and partners’ motives may be even more conflicted, contradictory and mutable when the rituals of romance are playing out in an environment already disrupted by older generations’ repertoire of ‘ghosting’,  ‘gaslighting’, ‘benching’ and ‘breadcrumbing’.

Above all we older people mustn’t underestimate Gen Alpha. They may sometimes be victims of the toxic aspects of digital culture, but they are also adept at coming to terms with it, manipulating it to their own advantage – or knowing when to reject it.

Avantika’s long feature on Gen Alpha is here…

Another way in which mainly younger creators and communicators are changing language is by way of Algospeak, the online code used to disguise messages and evade surveillance…

*In October I spoke to BBC Radio London about the phrase ‘six seven‘ (number one lookup in the US, above) which had now come to the attention of British media, having crossed over from TikTok performances and online posting to real-life irritation of UK teachers and parents. The meaningless phrase, unrelated to the very old expression ‘at sixes and sevens’ (in a state of confusion or disorder) which was used by Chaucer and Shakespeare, was being chanted with accompanying gestures (outstretched arms, palms upward) to tease, baffle and mock adults. Its young users were possibly unaware of its origins in the lyrics of a rap track by US artist Skrilla and its subsequent adoption by basketball stars and their followers.

Nobody as far as I know has yet mentioned – as my friend Nicky Hill reminded me – that the same numbers were already in use in South London in a more sinister context…

https://en.wikipedia.org/wiki/67_(group)

And, also on Twitter, from Celandine an intriguing tangential suggestion…

‘I saw something suggesting that parents take the opportunity to cite Deuteronomy 6:7! “You shall teach them (the Commandments) diligently to your children, and shall talk of them when you sit in your house, and when you walk by the way, and when you lie down, and when you rise.”’

On the eve of All Hallows Eve the Guardian continued the narrative…

https://www.theguardian.com/commentisfree/2025/oct/30/six-seven-meaning-slang

And for those who remember…

In November I was interviewed by Laura Cannon for BBC Bitesize, again about viral slang and trending youth language and its implications. Laura’s article is here…

6-7 and the ‘secret’ language of kids – BBC Bitesize

In December Dazed magazine featured its recommendations for Christmas gifts alongside a list of the year’s archetypes – the new identities which have replaced or reinforced the aesthetics, vibes and microtrends of 2024…

The 2025 Christmas archetype gift guide | Dazed

THE FIRST FEW WORDS

– of 2025

Back in December last year I wrote a second opinion piece on words of the year for the Conversation. You can find it here… *

At the end of January this year the Lexis Podcast team kindly invited me to discuss some of those words and why – if – they were really significant. We also looked at new terms recorded in 2025 so far, making a first attempt to explain and assess them, and to wonder which if any of them might endure. Our discussion, which went on for 40 minutes, is here…

…and, from February, a little puzzle for you. Can you unscramble and reassemble these two-word novelties? (Thanks to simplewordcloud.com)

It’s now July, and my attempts to go on recording this year’s wholly new, or reworked and updated terms and expressions have been interrupted by the need to react to the news-cycle – to the sinister euphemisms, avoidances and untruths perpetrated by war criminals, would-be dictators and their servants in the media. Examples of their language have been added my glossary of toxic terminology and the updated version is here…

John Belgrove reminded me that in May Donald Trump bragged of coming up with a new word – ‘a good word’, but the word in question was ‘equalising’. I have managed nonetheless, with the help of other friends and contacts on Twitter, BlueSky, Instagram and Facebook, to gather a few more examples of lexical innovation, candidates for an end-of year survey in due course…

But I would very much welcome suggestions of other new words and phrases, ideally together with their meanings and comments on their usage in context. All donations will be credited and donors thanked.

*https://theconversation.com/most-words-of-the-year-dont-actually-tell-us-about-the-state-of-the-world-heres-what-id-pick-instead-246190

A GLOSSARY OF WEAPONISED* WORDS, BREXITSPEAK and THE TOXIC TERMINOLOGY OF POPULISM

In 2018 I began collecting new and controversial language generated by the rise of conservative populism in the US and the UK, by pro- and anti-Trump sentiment in the US and by the divisions resulting from the UK’s Brexit vote. This is still a work in progress: the list of terms as it stands is below. An ideal glossary or lexicon would include detailed definitions and comments (for example, the second word in the list is my own invention, intended to describe a statement, act or policy showing effrontery, and itself a deliberate affront to a section of the population), dates of first use where traceable and a ‘lexical’ categorisation (into ‘jargon’, ‘slang, ‘catchphrase’, cliché, for instance). This more exhaustive treatment is beyond my resources for now, but googling the term in question will throw up examples which may be accompanied by dates and useful commentary.

In January 2024 I began to add words and phrases used by combatants and commentators in connection with the continuing ‘conflict’ in Israel, Palestine and Lebanon. Exactly one year later the ‘coup’, as some described it, enacted in the USA by Donald Trump and Elon Musk, featured new examples of distortion, euphemism and the language of rancour.

***Please do contact me with new examples, with comments and with criticism, which will be gratefully acknowledged and credited.***

Accelerationist

Accommodationist

Administrative detention

Affrontery

Agitators

Airfix patriotism

Alpha

Alt-centre

Alt-right

Amalek

Anglosphere

Annexationist

Anticipatory compliance/obedience

Antifa

Anti-growth coalition

Anywheres

Armed intervention

Asset

Astroturfing

Asylum shopping

Attitudinarian

Australia-style deal

Autohagiography

Backstop

Bad actors

Based

Bed-wetting

Beta

Beyond satire

Bike-shedding

Birtherism

Bitterites

Black hole

Black ops

The Blob

Blowback

Body count

Bot

Both-sidesism

Breadcrumbs

Brectum

Bregressive

Bregret(s)

Bremain

Brengland

Brexiles

Brexit dividend

Brexiteer

Brexit means Brexit

Brexit ultras

Brexmageddon

Brexmas

Brexodus

Brexomertà

Brexpats

Brexshit

Brextension

BRINO

Britain deserves better

Bubble

Butthurt

Cakeism

Calling out

Canada plus plus plus

Cancel culture

Candour deficit

Canzuk union

Casino capitalism

Centrist dad

Cherry-picking

Children of light

Chilling

Chumocracy

Churnalism

Civics

Civilian Security teams

Civility

Classist

Cliff-edge

Clown car

Clown country/state

Clusterbùrach

Coerced migration

Coercive diplomacy

Cognitive elite

Cognitive warfare

Collateral

Collective narcissism

Combative

Combat propaganda operative

Compassion deficit

Competing narratives

Concern(ed)

Concierge class

Confected fury

Conflicting accounts

Consequence culture

Copaganda

Cosmopolitan

Corbynista

Corporatocracy

Coup

Coup Klux Klan

Courtier journalists

Crash out

Cronyvirus

Crowdstrike

Crybaby

Cuck

Culturalism

Cultural marxist

Culturally coherent

Culture warrior

Dark forces

Datagrab

Dead cat strategy

Death cult

Deepfake

Deep state

Defund

DEI (Diversity, Equity, Inclusion)

DEI items

Delegitimizer

Demilitarization

Democide

Deplorables

Detained

DEXEU

‘Dies’

Disappeared

Disaster capitalism

Discourse engineering

Disinformation

Divorce bill

Do-gooder

Dogpile

Dog-whistle

Doom loop

Double down

Doxxing

Drain the swamp

DREAMer

Dumpster fire

Echo-chamber

Economic nationalism

Economically inactive

Educide

Elite

Empty chair

Enablers

Enemies of the people

English exceptionalism

Ergo decedo

Establishment

Ethnics

Ethnonationalist

Ethno-state

Exchange of fire

Expert

Factuality

Fake news

Fall off a cliff

False flag operation

Fash-adjacent

Fashy

Fauxlanthropist

FBPE

Feminazi

Fifth column

Finger-sniffer

Firehosing

Flextension

Flooding the zone

FluTruxKlan

Fractionate

Fratriarchy

Frictionless

Frit

Frontlash

FUD

Gammon

Gammonista

Gangster state

Genocide Joe

Get it done

Getting the barnacles off the boat

Gimmegrant

Girly swot

Global Britain

Globalist

GNU

Grievance studies

Grumpy retiree

Guardianista

Hard Brexit

Hate goblin

Hatriot

Headroom

Headwinds

Henry VIII powers

Heterophobic

High-vis nazis

Hobbit

Homonationalism

Hopepunk

Hose it down

Humanitarian bridge

Hybrid threats

Identitarian

Idiocracy

Illuminati

Incel

Indications

Indicative vote

Individual-1

Intentional explosion

Intifada

Irrational exuberance

Jambon jaunes

Jexodus

Kayfabe

Keirmacht

Kicking the can down the road

Kindercoup

King baby

Kipper

Kipper moment

Kleptofascist

Kompromat

Lamestream media

Lawfare

Leave means leave

Leftwaffe

Legitimate concerns

Lentil-weaving

Lesser mortals

Lethal aid

Level up

Lexit

Libertarian

Libtard

Loss of life

“Lost their lives”

Limited ground operation

Limp-wristed

Little Englander

Lolcow

Londongrad

Londonistan

Long Corbyn

Long coup

Low-energy

Luftwaffle

MAGA

Magic Grandpa

Magic money tree

Majoritarian

Man-baby

Mangina

Manosphere

Manufactured consent

Masculinist

Matrixed

Maybot

Meaningful vote

Meat wave(s)

Mediaeval methods

Melt

Meninist

Mercurial

Metropolitan

Microaggression

Militarised nostalgia

Milkshake(d)

Mindless compassion

Ming vase

Mischievous

Mishap

Missing

Momtifa

Moral clarity

Moral emptiness

Moral grandstanding

MSM

Nakba 2

Nanny state

Nativist

Necrocapitalism

Necropolitics

Neglexit

Neon nazis

Nerd Reich

Neurotic elite

Neutrollization

No-deal

No-platforming

Normie

Nudgism

Obey in advance

Offence archaeology

Operational matter

Operation Red Meat

Operation Save Big Dog

Optics

Ordeals

Ostentatious meekness

Oven-ready

Over-briefed

Overly purist

Overton window

Palaeoconservative

Partygate

Pearl-clutching

Penumbral jobs

People’s vote

Performative allyship

Performative cruelty

Pile on

Political correctness

Political gospel

Polycrisis

Post apocalyptic warlord

Post-liberal

Postmodern

Posttext

Post-truth

Poverty porn

Prebunking

Pre-emptive strike

Price cap

Project Fear

Protesters

Prozac leadership

Pugnacious

Punchy

Purity of arms

Push (BBC euphemism for armed incursion, invasion)

Pushback

Put/stick that on the side of a bus

QAnon

Quitlings

Rabble

Race to the bottom

Rage bait

Rage farming

Rampdown

Red lines

Red pill

Red wall

Regrexit

Rejoiner

Re-leaver

Relocate

Remainiacs

Remain plus

Remigration

Remoanathon

Remoaner

Remove kebab

Replacement theory

Reply deboosting

Reputation laundering

Resistance

Restorative nostalgia

Retconning

Revoker

Roll back

Rootless

Row back

Russian asset

Saboteur

Sadopopulism

Safe space

Scumbag centrism

#ScumMedia

Sealioning

Sensitivity reader

Shadow blocking

Shallowfake

Shill

Shire

Shitposting

Shitshow

Showboating

Shylock

Sick-note culture

Singapore-on-Thames

SJW social justice warrior

Skilling up

Skunked term**

Slave populace

Sleaze

Snowflake

Sobersides

Sockpuppet

Soft border

Soft Brexit

Somewheres

Sovereignty

Soy-boy

Spartan phalanx

Spiv

Star Chamber

Starmergeddon

Stenographer

Sticking point

Strategic self-abasement

Stunning proposal

Sunlit uplands

Supermajority

Surgical strike

Svengali

SWERF

TACO

Taking back control

Tankie

Targeted individual

Targeted strike

Technofeudalism

Tender-age shelter

“Tensions rise”

Terf

Terminability

The other team

Throw under the bus

#tfg, ‘the former guy’

Tick tock

Tigger

Tofu-eating

Tone deaf

Tone policing

Tory scum

Toxic positivity

Transactional

Transition period

Trexit

Triangulation

Tribal(ism)

Trickle-down pathology

Troll farm/factory

Trumpcession

Trump slump

Truth-squadding

Tufton Street

Tu quoque

Two-tier policing

Unconfirmed reports

Unicorns

Unpopulism

Unrest

Unspin

Urban

Values voter

Vassal state

Verbal incontinence

Vice-signalling

Vigilante journalism

Village idiot

Virtue-signalling

Voluntary emigration

Walk back

War cabinet

War of extraordinary civilian casualties (Guardian euphemism for genocide)

Watch-list

Weaponised*

Wedge issues

West(s)plaining

Whataboutery

White supremacist

Will of the people

With a heavy heart

Woke

Woke mind virus

Wokerati

Wokescold

Woketard

Woke warriors

Woke-washing

Womp womp

Workington man

Yoghurt-knitting

Zealot

I’m grateful especially to the many contacts on Twitter who have already contributed to this modest project, particularly Duncan Reynolds @duncanr2, and will credit them all by name/handle when a final version is published.

I’m also very grateful to Rob Booth and the Guardian who, in October 2019, wrote about the glossary and its topicality in increasingly conflicted times:

https://www.theguardian.com/politics/2019/oct/05/brexitspeak-brexit-vocabulary-growing-too-fast-public-keep-up

And to Carlos Fresneda for this piece in El Mundo:

https://www.elmundo.es/internacional/2019/10/17/5da765cf21efa0eb618b4680.html

Artist Simon Roberts has kindly shared with me his artworks based on his own lexicon of Brexit language:

Between the Acts, Part II – The Brexit Lexicon

For readers, students, and researchers interested in or working with this topic here are some of the other articles and sources to consider…

In February 2017 The New European published its own very useful lexicon, from which I have drawn, gratefully but without permission :

https://www.theneweuropean.co.uk/culture/the-new-lexicon-of-hate-a-disturbing-a-z-of-alt-right-language-1-4894833

And the BBC listed many of the technical – and some less technical – terms associated with Brexit earlier this year:

https://www.bbc.com/news/uk-43470987

Last year Karl McDonald discussed the language used by Labour party leftists in the i newspaper:

https://inews.co.uk/news/politics/slugs-melts-inside-language-culture-corbynite-left/

And here’s Helen Lewis in the New Statesman on incivility in the UK:

https://www.newstatesman.com/politics/uk/2018/08/how-britain-political-conversation-turned-toxic

And Philip Seargeant on ‘fake news’:

In November 2018 The Guardian published a useful ‘jargon-buster’ guide to the terms being used at this late stage of (or impasse in, if you prefer) UK-EU negotiations:

https://www.theguardian.com/politics/2017/jun/19/brexit-phrasebook-a-guide-to-the-talks-key-terms

Here Renee DiResta describes the ongoing ‘Information War(s)’ of which the manipulation of language is one component:

The Digital Maginot Line

I have only just come across this perceptive essay from 2017, by Otto English on his Pinprick blog, in which he coins the terms Ladybird libertarian and Ronseal academic:

Ladybird Libertarians: Dan Hannan, Paddington and the pernicious impact of 1970s children’s literature on Brexit thinking

In January 2019 James Tapper contributed this very perceptive assessment of Brexit metaphors:

And in March, more from the BBC:

http://www.bbc.com/culture/story/20190314-how-brexit-changed-the-english-language

In July 2019 the FT ran an interesting review of Boris Johnson’s press articles as precursors of ‘fake news’:

https://www.ft.com/content/ad141e8a-976d-11e9-9573-ee5cbb98ed36

And in October of the same year David Shariatmadari and Veronika Koller considered Brexit metaphors:

Brexit and the weaponisation of metaphor

*The progressive weaponisation of language is discussed here by Justin Strawhand:

https://www.huffpost.com/entry/weaponized-language_b_1380788

In an update from November 2023 New Lines Magazine addressed the distorted, conflicted language employed in describing Israel’s response to Hamas:

https://newlinesmag.com/argument/language-is-a-powerful-weapon-in-the-israel-palestine-conflict/

**’Skunked terms’ are words or expressions undergoing a controversial change in meaning. Examples are ‘liberal’ and ‘libertarian’ which have transitioned from referring to leftist, progressive or centrist positions to denote neo-conservative or alt-right affiliations. Nearly two years on from my original post the useful designation ‘anglosphere’, describing English-speaking nations with shared cultural features, has been co-opted by far-right nativists in the UK to promote a supremacist ideology.

Image result for Brexit graffiti

As a further footnote, this from Twitter in November 2020 (thanks to Alan Pulverness), a reminder that weaponised words may also be frivolous – even puerile:

Image

Looking back to 2016, a prescient tweet by Gary Kasparov:

Image

At the end of 2022 my friend and collaborator Dan Clayton wrote, for Byline Times, about the latest iteration of toxic terminology and rhetoric: the demonising of refugees and migrants:

In early 2024 I belatedly learned of an interestingly tendentious and sententious glossary purporting to list and explain the words used by the ‘woke’. This, compiled by Dr James Lindsay, critically examines key terms relating to gender studies, critical race theory and identity politics in the US context:

And in May 2024 Amanda Montell described in The Guardian how politicians and influencers deploy cliches in online discourses:

https://www.theguardian.com/books/article/2024/may/20/the-big-idea-the-simple-trick-that-can-sabotage-your-critical-thinking?CMP=share_btn_url

In June 2025 the Centre for Media Monitoring published its analysis of the BBC‘s coverage of the devastation of Gaza:

Later in June, as Israel and Iran exchanged fire, Assal Rad noted the double standards employed in reports of the conflict:

The language of manufacturing consent:

🇮🇱

: Preemptive strikes

🇮🇷

: Escalation

🇮🇱

: Warns

🇮🇷

: Threatens

🇮🇱

: Targets

🇮🇷

: Attacks

🇮🇱

: Government

🇮🇷

: Regime

🇮🇱

: Right to self-defense

🇮🇷

: Condemnations

🇮🇱

: Sophisticated military (has nukes)

🇮🇷

: Nuclear threat (has no nukes)

THE SLANG AND NEW LANGUAGE ARCHIVE

A research portal for scholars, the press and the public

The Slang and New Language Archive was created in 1994 while I was Director of the Language Centre at King’s College London. The archive, consisting of a small library of books and periodicals and a number of databases and sub-directories, was designed as a repository for the collection, storage and dissemination of new language, in particular examples of nonstandard varieties of English such as slang, jargon and buzzwords. The archive was later expanded to take in examples of media language, political language, linguistic curiosities and etymologies. It remains a resource, unique in the UK and not-for-profit, assisting researchers, students, teachers and journalists, as well as non-specialists, in accessing information about aspects of contemporary language that are under-represented in traditional dictionaries and reference works.

This link will take you to the Archive webpage at King’s College, where there are further links to relevant articles and published sources…

https://www.kcl.ac.uk/research/slang-and-new-language

Glossaries from the archive may be accessed on this site by entering keywords, such as slang, jargon, MLE (Multiethnic London English), familect (highly colloquial language used in the home), coronaspeak (language related to the COVID-19 pandemic) and weaponised words (the contentious language of Brexit, populism and biased reporting) and slurs (racist and misogynist terms) in the search box. Once you have accessed a post of interest, check the tags and categories at the foot of the page for other articles or glossaries on the same topic.

Two of the larger archive datafiles are hosted on Aston University’s Institute of Forensic Linguistics Databank site. These are a glossary of current youth slang

https://fold.aston.ac.uk/handle/123456789/4

And a glossary of UK street slang, rap music and gang terminology

https://fold.aston.ac.uk/handle/123456789/5

Please note that the King’s archive focuses principally on contemporary language, that is terms used from the twentieth century to the present day. If you are interested in historical slang, I strongly recommend the monumental work by my associate, the British lexicographer Jonathon Green. His dictionary, now generously freely available online, lists current and historical slang terms with timelines and citations illustrating their usage and development…

https://greensdictofslang.com/

For more information, for queries, or to donate examples of language, contact me via this website or via the King’s College webpage. I’m on Twitter as @tonythorne007 too.

In terms of new slang and nonstandard language there are few reliable resources online. In February 2025, however, US publisher Merriam-Webster launched their own slang dictionary. You can find it here…

https://www.merriam-webster.com/slang

Among the many more informal glossaries and wordlists of slang posted on the internet in 2025, this review of slang in English schools is unusually comprehensive and accurate…

https://teachertapp.com/uk/articles/down-with-the-kids-slang-in-british-classrooms-2025/

QUIET QUITTING, TWO-TIMING OR DOUBLEDATING?

A (nearly) new lexicon describes new attitudes to work

I spoke last week to Financial Times journalist Emma Jacobs about so-called ‘Polygamous Working‘, part of the new vocabulary of the workplace generated by younger employees still coming to terms with a post-pandemic work-life balance. Holding a second job is not necessarily illegal providing it is disclosed, but recent reports describe hundreds of public sector workers in the UK illicitly receiving multiple salaries from simultaneous jobs. When the idea of a polyamorous workplace first surfaced three or so years ago, some business gurus hailed it as a positive trend: “Polygamous careers are giving workers the opportunity to hone new skills, fully leverage their knowledge, and pursue numerous interests at once. The emphasis is on contributing to various projects and roles, as opposed to working exclusively with a specific employer.”

In this context new expressions like “quiet quitting” and “task masking” are gaining traction. They are, says writer and lexicographer Tony Thorne, “self-consciously coined and promoted like memes”, designed to go viral. Thorne thinks this suggests the young people using them are not lazy, but “more resistant to accepting traditional notions of work, workplaces and work etiquette”. Perhaps no surprise, given they grew up in the aftermath of Brexit and the pandemic.

Gen Z in particular have a different take on work-life balance and really on the nature of work itself I think. They approach these things as part of a wider matrix of lifestyle modes, (self-help and self actualisation and curating relationships) what they call ‘vibes’ and ‘aesthetics’ and performative behaviour. We can’t forget also that their behaviour even at work often reflects their pervasive use of irony, sarcasm and self-parody.

This is reflected in the terminology they have adopted of course. I think another aspect which hasn’t been discussed much is the fact that GenZ have not been conditioned by the sort of corporate culture, office culture or lingering work ethic that Gen X and millennials were conditioned by. Add to this the fact that they more than anyone have undergone the disruption caused by Brexit, the aftermath of austerity and the pandemic and so may be more resistant to accepting traditional notions of work, workplaces and work etiquette.

There is yet another way in which things are different for younger cohorts. They exist in a globalised online reality where trends in behaviour are not driven by ‘authorities’ or ‘professionals’ but by influencers and content creators chasing clicks and clout. New expressions are not just words or phrases which spread by word of mouth but may be self consciously coined and promoted like memes. They may not simply exist as sounds and spellings but also accompany images and soundtracks (as on TikTok). Linguists might call them ‘multimodal‘.

Neither the notions they describe or the terms themselves are completely new. Back in 2005* I reported ironic office slang such as ‘FaceTiming’, just putting in an appearance to suggest dedication to the job, ‘Sunlighting’ (like moonlighting), aka ‘Dual Jobbing‘, doing a quite different job one day a week. ‘WFH‘, ‘Remote Working‘, ‘Hybrid Working‘ – and ‘Side Hustles‘ – were later coinages prompted by enforced flexibility. The end of the pandemic saw the ‘Great Resignation‘ of 2021 as disillusioned workers supposedly abandoned unfulfilling careers en masse. Employers were encouraged to promote ‘Cross-Skilling‘, training staff to perform a wider range of functions, and ‘Job-Crafting‘, allowing employees to design their own roles.

Emma’s article with contributions from Bobby Duffy, director of the Policy Institute at King’s College London, is here…

https://www.ft.com/content/e3349ea5-50f7-447b-b466-750e038f706b

*From Shoot the Puppy -A survival guide to the curious jargon of modern life

Writing in the Conversation, John-Paul Byrne has more on the ‘quiet quitting ‘phenomenon…

The trend for ‘quiet’ and ‘soft’ quitting is a symptom of our deteriorating relationship with work

GOING VIRAL, GOING GLOBAL

youth slang crosses world englishes

Last week I was interviewed by two young journalists about the pervasive slang generated by Gen Z and Gen Alpha. Interestingly both journalists are operating outside the US/UK matrix from which much of this language variety emanates. Interestingly too, both journalists asked similar questions about the latest linguistic novelties and how we might respond to them. Kanika Saxena‘s piece appeared in the Economic Times of India, and my contribution is here…

1. How do new slang words take root in a generation? Do they slowly build momentum, or does one viral moment suddenly put them everywhere?

In the past it could take some time for slang to escape from the local social group (‘in-group’ or ‘peer group’: a group of friends, a gang, fellow workers, etc.) where it originates into the outside world, then to spread by word of mouth into other parts of society, finally perhaps being picked up by the entertainment or print media. Nowadays this process has been massively speeded up by messaging and the internet, so that a novel term can go viral and reach beyond its original community almost instantaneously. New expressions can spread via social media and platforms like TikTok, Youtube, InstaGram right across the ‘anglosphere’ and go global.

2. Some words stick around for decades, while others vanish overnight. What makes certain slang words stand the test of time?

Linguists have tried to analyse why some terms become briefly fashionable and then disappear while others endure. There don’t seem to be any rules that govern why this happens. Some experts think that words which convey important social or technological innovations or that reflect current ‘moods’ or preoccupations are likely to have a longer appeal, but there’s no real proof of this. It could also be because a word relates to important social behaviour or relationships: insults, terms of endearment, ‘dating’ language, complaining, identity labels, for example, have to be reinvented for each successive generation, then persist until their users mature or grow older.

3. With social media throwing new words at us daily, are we actually creating more slang than before, or does it just feel that way because everything is amplified online?

It’s hard to say if the total ‘volume’ of slang has increased because, in the past at least, it was impossible to quantify it. What is definitely true is that slang has for some time become more accepted by mainstream media whereas it used to be censored or ignored. We also have the very new phenomenon whereby influencers, TikTok stars and content creators are using online resources to consciously, deliberately create, promote and spread new terms, so slang is no longer just coming ‘up from the streets’ (or spread via music, TV and movies) but is a commodity exchanged and pushed to gain prestige or sell oneself.

4. Older generations always seem skeptical of new slang—until, of course, they start using it too. What’s the secret to a word crossing generational lines?

Parents, teachers and ‘authority figures’ generally start by decrying younger people’s language and avoiding or ignoring it or trying to ban it. (This isn’t really justified by the way: slang may be seen as socially marginal but is not technically deficient or defective language and uses the same techniques as poetry or literature) But if a term is adopted by the media (‘woke’ is an example) they may in a few cases start to use it themselves. Technological terms (‘spam’, ‘troll’ etc.) and lifestyle jargon may be invented or used by older speakers. I always warn parents, though, not to try and imitate their kids by borrowing their slang. In the kids’ own language this is extremely ‘cringe’.

My second interview was with Austėja Zokaitė who is based in Lithuania and it appears in the online magazine Bored Panda, an arresting and anarchic daily roundup of the latest viral images, memes and commentary on internet culture. The whole report is here, with my comments interspersed with the succession of visual elements…

This IG Page Shares “Hard” Images, And Here’s 30 Of The Most Unhinged

Two weeks later I took part in a podcast on the subject of Slang, hosted by US students Sophie Xie and Andrea Lee. Our discussion is here…

Dang, What’s That Slang? by Andrea Lee

INITIAL FINDINGS

more updates on 2025’s language landscape

Once again, I’m very grateful indeed to Randoh Sallihall of Unscramblerer.com for sharing his data on language usage online. I previously posted his analysis of last year’s slang lookups (online searches)* and this time his findings reveal the most popular internet text abbreviation lookups in 2025 so far, for the UK and the USA. I was amused to see SMH (‘shaking my head‘) featuring high in both lists. A few years ago I confidently stated in a BBC radio interview that this stood for ‘same here’ – as I had just been informed by a group of schoolkids. I was immediately and publicly corrected – and shamed – by presenter Anne McElvoy and invited journalist Hannah Jane Parkinson and the bitter experience has stayed with me.** It may be culturally significant also that Britain’s favourite apology – in the form of SOZ – doesn’t feature at all on the American list.

“Analysis of Google search data for 2025 so far reveals the most searched for text abbreviations in the UK.”

Most searched for text abbreviations in the United Kingdom:

1.      POV (39 000 searches) – Point of view.

2.      SMH (34 000 searches) – Shake my head.

3.      PMO (28 000 searches) – Put me on.

4.      ICL (17 000 searches) – I Can’t Lie.

5.      OG (16 000 searches) – Original gangster.

6.      OTP (16 000 searches) – One true pairing.

7.      NVM (13 000 searches) – Never mind.

8.      TM (11 000 searches)- Talk to me.

9.      SN (7 000 searches) – Say nothing.

10.   BTW (6 000 searches) – By the way.

11.   KMT (6 000 searches) – Kiss my teeth.

12.   FS (6 000 searches) – For sure.

13.   WYM (6 000 searches) – What you mean.

14.   HRU (6 000 searches) – How are you?

15.   ATP (5 000 searches) – At this point.

16.   SYBAU (5 000 searches) – Shut your b—h ass up.

17.   IGHT (5 000 searches) – Alright.

18.   ONB (4 000 searches) – On bro.

19.   WSP (4 000 searches) – What’s up?

20.   TY (4 000 searches) – Thank you.

21.   SOZ (3 500 searches) – Sorry.

22.   IDC (3 000 searches) – I don’t care.

23.   LDAB (3 000 searches) –  Let’s do a b-tch.

24.   PFP (3 000 searches) – Picture for proof.

25.   IBR (3 000 searches) – It’s been real.

26.   IYW  (3 000 searches) – If you will.

27.   TB (2 500 searches) – Text back.

28.   FYI (2 500 searches) – For your information.

29.   GTFO (2 500 searches) – Get the f–k out.

30.   HY (2 000 searches) – Hell yeah.

Most searched for text abbreviations in the United States:

1.      FAFO (254 000 searches) – F–k around and find out.

2.      SMH (166 000 searches) – Shake my head.

3.      PMO (101 000 searches) – Put me on.

4.      OTP (95 000 searches) – One true pairing.

5.      TBH (93 000 searches) – To be honest.

6.      ATP (85 000 searches) – At this point.

7.      TS (79 000 searches) – Talk soon.

8.      WYF (76 000 searches) – Where are you from.

9.      NFS (75 000 searches) – New friends.

10.   ASL (65 000 searches) – As hell.

11.   POV (63 000 searches) – Point of view.

12.   WYLL (59 000 searches) – What you look like.

13.   FS (58 000 searches) – For sure.

14.   FML (56 000 searches) – F–k my life.

15.   DW (55 000 searches) – Don’t worry.

16.   HMU (54 000 searches) – Hit me up.

17.   ISO (53 000 searches) – In search of.

18.   WSG (50 000 searches) – What’s good?

19.   IMO (48 000 searches) – In my opinion.

20.   MK (45 000 searches) – Mmm, okay.

21.   ETA (40 000 searches) – Estimated time of arrival.

22.   ICL (37 000 searches) – I Can’t Lie.

23.   MB (37 000 searches) – My bad.

24.   STG (29 000 searches) – Swear to god.

25.   ION (28 000 searches) – In other media.

26.   PFP (27 000 searches) – Picture for proof.

27.   NTM (27000 searches) – Nothing much.

28.   DTM (26 000 searches) – Doing too much.

29.   TTM (26 000 searches)- Talk to me.

30.   MBN (25 000 searches) – Must be nice.

31.   ETC (24 000 searches) – And the rest.

32.   BTW (23 000 searches) – By the way.

33.   WFH (21 000 searches) – Work from home.

34.   GMFU (20 000 searches) – Got me f—-d up.

35.   NGL (19000 searches) – Not gonna lie.

36.   SYBAU (19 000 searches) – Shut your b—h ass up.

37.   BTA (17 000 searches) – But then again.

38.   SB (17 000 searches) – Somebody.

39.   HBD (16 000 searches) – Happy Birthday.

40.   PMG (15 000 searches) – Oh my god.

41.   HY (15 000 searches) – Hell yeah.

42.   TMB (11 000 searches) – Text me back.

43.   WYS (10 000 searches) – Whatever you say.

44.   GNG (9 000 searches) – Gang (close friends or family).

45.   IKTR (8 000 searches) – I know that’s right.

46.   IKR (7 000 searches) – I know, right?

47.   ARD (6 000 searches) – Alright.

48.   IFG (5 500 searches) – I f—–g guess.

49.   HN (4 000 searches) – Hell no.

50.   TTH (3 000 searches) – Trying too hard.

A spokesperson for Unscramblerer.com commented on the findings: “Text abbreviations are the secret language of the internet. You could even call them an integral part of social media culture. Snappy, always changing and hard to understand. Texting abbreviations is all about saving time and appearing cool. Keeping up to date with the newest trending abbreviations is no easy task. Old meanings can change while new abbreviations are created. A recent study found that abbreviations might not be as cool as people think. Using abbreviations makes the sender seem less sincere. This also leads to lower engagement and shorter responses. There is nothing wrong with using abbreviations in casual conversations with friends and family. However it is best do draw a line for professional conversations. Context matters.”

Research was conducted by word finding experts at Unscramblerer.com.

We analyzed 01.01.2025 -05.03.2025 search data from Google Trends for terms related to text abbreviations.

Methodology: We used Google Trends to discover the top trending text abbreviations and Ahrefs to find the number of searches. America’s most popular text abbreviations can be discovered in Google Trends through the keyword variations of ‘meaning text’. Abbreviations are used most often on social media and texting. The 2025 top trending abbreviations are the least understood. People have to search for their meaning (example ‘TBH meaning text’). Ahrefs shows many variations of meaning searches like ‘text meaning’ or ‘means in text'(example ‘PMO meaning in text’) and similar keyword combinations(example ‘what does SMH mean in text’). We added up 100 search variations of top text abbreviations.

I was very grateful, too, when Claire Martin-Tellis of content marketing and digital PR specialists North Star Inbound contacted me with an update, again from the USA, on attitudes to outdated slang

“As new slang terms like “Beta,” “GYAT,” and  “Skibidi,” continue to surface, it’s enough even to make Gen Z feel old! Language learning app Preply asked Americans of all ages to weigh in on their favorite era of slang. Here is what decade reigns supreme:

  • Over ⅓ of Americans say the 1990s is their favorite decade for slang.
  • Men surveyed preferred the 1970s while women preferred the 1990s.
  • “Baloney,” “take a chill pill,” and “bogus” are the three most popular slang terms Americans want to see come back.

*https://language-and-innovation.com/2024/11/18/the-search-for-slang/

**the embarrassment is still audible here…https://www.bbc.co.uk/programmes/b06vs6g2

LANGUAGE REPLICATION – OR LANGUAGE INNOVATION?

Are the machine learning tools and chatbots that work with human language creating, or just impersonating?

I spoke this week to Rob Booth, the Guardian’s UK Technology Editor, about the latest interfacing between AI and human language interactions, a topic I am only just beginning to explore. Rob’s perceptive analysis with contributions from my friend Professor Rob Drummond, is here…

https://www.theguardian.com/society/2024/dec/11/ai-tone-shifting-tech-could-flatten-communication-apple-intelligence

A few days earlier French business journalist Jacques Henno asked if AI could now actually create language rather than merely replicate it or imitate it…

“I’d like to know your opinion on the impact of generative AI tools on language evolution. These tools, such as OpenAI’s ChatGPT, Google’s Gemini, Anthropic’s Claude, and others, don’t invent but simply reproduce learned content. What do you think their influence will be on written and spoken language?”

Primitive versions of AI have been used for some time to generate new terms, notably brand names and product names. These can be generated by entering desirable associations or attributes plus related names or keywords into an engine which will produce new combinations of words or completely new items of vocabulary.

Likewise, there have been business or corporate ‘jargon or buzzword generators’ in use for some years which can be activated for fun to create new (and supposedly absurd or comical) terms. https://www.feedough.com/business-jargon-generator/

AI can already create new languages in order to translate or interpret communication systems and to mediate between other non-human ‘languages’ such as programming languages or symbolic or mathematical systems. These languages however are not generally usable for normal human interactions and not normally recognisable as languages by non-specialists 

More recently, more powerful and sophisticated AI tools have been introduced which claim to work with the technical mechanisms and structures of existing languages (the ways in which English, French, Russian, etc. form words and attach word-endings, change nouns to verbs, for example and the way in which Hungarian, Mandarin, Hindi, etc. arrange words or characters in order) and with their use of metaphor and semantic shift (extending the meaning of a concept). These can already create new words. Two examples are here…

https://alibswrites.medium.com/times-are-changing-will-ai-create-our-new-vocabulary-12f6f68a7890

https://www.independent.co.uk/tech/ai-new-word-does-not-exist-gpt-          2-a9514936.html

But despite the sophistication of the latest Large Language Models and language-generating AI tools, there are still predictable areas in which the material they produce is often deficient or defective. Real language innovation does not just involve using the structures of existing languages or adding prefixes or suffixes to existing words or combining syllables in a new way. Even a machine-learning tool which can understand and manipulate metaphor, synonymy, imagery can’t yet grasp the subtleties of human inventiveness, or the psychological and physical processes involved in making new language which is genuinely usable, pleasing, convincing and ‘authentic’. Creating new words involves – as in literature, poetry but also in everyday professional or social life – drawing on cultural allusions, references to shared values, knowledge of fashion, beliefs, cultural history, local conditions, jokes and styles of humour, etc. Apart from style, register, tone, appropriacy (tailoring one’s choice of words to the context in which they are used), etc. another key linguistic concept that AI will struggle to cope with is ‘implicature’, the human tendency to express things indirectly, to infer.

Another aspect of language which AI finds it hard to understand or replicate is what is called ‘phonaesthetics’ or ‘sound symbolism’. This involves the sounds and pronunciations (and the look of the word on the page too) of words and the psychological effects these sounds have on the mind of the hearer, many of the words created by AI just don’t sound or look like real words. This has been a problem in generating brand names or product names, many of which look or sound ugly and unappealing to potential consumers or users.

There are so many tiny social cues in real-life human interactions that are not always pattern behaviour or even precedented and are often based on abstract ideas. They may also involve allusion, shared cultural reference and often irony and humour. There is also something called ‘embodied metaphoricity’: “For a mental representation to be “embodied” in the sense most commonly invoked by metaphor researchers, it must be instantiated at least in part by a simulation of prior or potential bodily experiences, within modality-specific components of the brain’s input and output systems (e.g., visual cortex, motor cortex; Barsalou 1999)”, in other words understanding is ‘seeing’, knowing is ‘grasping’. Humans activate this instinctively and can reflect on it intellectually: AI in its present incarnations can’t do either.

Developers and programmers are well aware of many, if not all, of these problem areas and are energetically attempting to address them…

https://www.sapiens.org/language/ai-oral-languages/

My observations so far have been based on a very superficial understanding of exactly how large language models and generative AI work. I’m therefore very grateful indeed to Dr Joe McIntyre for his recommendation of this explanatory guide…

https://arstechnica.com/science/2023/07/a-jargon-free-explanation-of-how-ai-large-language-models-work/

I’m recommending a role for linguists in monitoring AI’s ability to understand or replicate the nuances of human speech. This project is pioneering a sociolinguistic approach to the question of bias in AI-generated content…

https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2024.1472411/full

Very belatedly I asked ChatGPT itself to tell me about AI’s drawbacks in handling or reproducing human language. It offered me two responses which I reproduce here…

The first response…

AI has made great strides in handling human language, but it still has notable weaknesses:

  1. Context Limitations: AI struggles with maintaining long-term context in lengthy conversations or documents, which can lead to inconsistencies or irrelevant responses.
  2. Ambiguity: Human language is often ambiguous, and AI might misinterpret subtle nuances, slang, or idiomatic expressions, leading to incorrect or nonsensical outputs.
  3. Lack of World Knowledge: While AI can access vast amounts of information, it lacks true understanding or lived experience, which can make it difficult to handle subjective, emotional, or cultural contexts.
  4. Subtlety in Tone: Sarcasm, irony, and humor are challenging for AI to detect and respond to appropriately, especially without clear contextual markers.
  5. Ethical Judgment: AI can falter in making ethical or moral judgments when the appropriate course of action requires nuanced human values or cultural sensitivity.
  6. Bias in Training Data: AI can inherit and even amplify biases present in its training data, leading to unfair or problematic language generation.
  7. Difficulty in Creative Expression: While AI can mimic creative writing styles, it often lacks originality, deeper insight, or the emotional depth that comes from human creativity.
  8. Overconfidence: AI can confidently provide incorrect answers because it doesn’t inherently know when it lacks the required knowledge or context to respond accurately.

The second response…

1. Lack of True Understanding

  • AI processes language based on patterns and statistical associations but doesn’t truly “understand” meaning or context the way humans do. This can lead to misunderstandings or inappropriate responses in nuanced situations.

2. Ambiguity in Context

  • Human language is highly context-dependent. Ambiguities, idioms, sarcasm, or double meanings can confuse AI, especially if the context is insufficient or contradicts typical patterns.

3. Inability to Handle Novelty

  • AI struggles with completely new or rare scenarios that lack sufficient training data. If faced with language or ideas it hasn’t been trained on, it might provide irrelevant or nonsensical responses.

4. Bias in Language Models

  • AI models can inherit biases from their training data, leading to biased or insensitive outputs. These biases reflect the data sources used and are difficult to eliminate completely.

5. Rigidity in Logic

  • AI often interprets instructions literally and may struggle with flexible or creative problem-solving, especially when the input is vague or requires unconventional reasoning.

6. Lack of Emotional Intelligence

  • While AI can mimic empathetic responses, it lacks genuine emotional awareness or the ability to fully grasp the emotional subtext in complex human interactions.

7. Limited Common Sense

  • Despite improvements, AI still struggles with common-sense reasoning, particularly when it involves understanding the physical world or day-to-day human experiences.

8. Overconfidence in Responses

  • AI can sometimes generate confident-sounding but incorrect or misleading answers, as it has no internal mechanism to distinguish between what it knows well and what it doesn’t.

9. Difficulty with Long-Term Coherence

  • Maintaining coherence in extended conversations or texts can be challenging for AI, especially when the discussion involves multiple threads or evolves over time.

10. Cultural and Linguistic Nuances

  • AI may falter in understanding or generating culturally specific expressions, regional dialects, or less commonly spoken languages, especially if training data is sparse.

I later spoke to author Mark Piesing on the same subject, and his very informative review in the Bookseller is here…

https://www.thebookseller.com/comment/servant-or-master

Dan McIntyre (a Twitter mutual) is among the first linguists to subject the capacities of large language models to expert analysis…

https://www.sciencedirect.com/science/article/pii/S0378216625000323

And in May 2025 I came across this interesting study which, at first sight, seems to suggest hitherto unexpected capacities for AI in precisely the areas suggested as deficient above…

In September 2025 Wikipedia published an excellent review of writing styles and linguistic cues detectable in AI-generated texts…

https://en.m.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing

THE SEARCH FOR SLANG

Researching and tracking the latest slang can now draw upon statistical analysis of online data.

As 2024 draws to its end and talk among lexicographers, culture journalists and language buffs turns to ‘words of the year’, I’m immensely grateful to Randoh Sallihall of Unscramblerer for providing me with his datasets showing lookups (Google searches) for the most popular recent slang expressions…

Most searched for slang words in United Kingdom:

1.      Gaslighting (170 000 searches) – a type of manipulation that makes you doubt your memories and feelings. The person doing it may lie and deny things.

2.      Skibidi (125 000 searches) – refers to a viral internet trend featuring surreal, animated videos of singing toilets and dancing heads, popularized on platforms like TikTok for its bizarre humor.

3.      Pookie (47 000 searches) – to show endearment and affection. Used for a close friend, partner or family member. A playful way to say someone is special.

4.      Hawk tuah (40 000 searches) – imitative of a spitting sound. The catchphrase originates from a viral street interview conducted in June 2024 with Haliey Welch, who stated that her signature move for making a man ‘go crazy’ in bed was to ‘give him that hawk tuah and spit on that thang’.

5.      Sigma (37 000 searches) – refers to an independent, self-reliant person who operates outside traditional social hierarchies, often described as a ‘lone wolf.’

6.      SMH (31 000 searches) – internet slang for ‘shaking my head’. Used to express disapproval or disappointment.

7.      Demure (26 000 searches) – reserved, modest or shy in manner or appearance. The TikTok user Jools Lebron made a series of viral videos using the phrase “very demure”. This trend gave the word a playful slang meaning. She uses it to assess appropriate makeup and fashion choices in various settings.

8.      Rizz (25 000 searches) – style, charm or attractiveness. The ability to attract a romantic partner and make others like you.

9.      Dei (17 000 searches) – diversity, equity, inclusion. A family friendly way of saying woke.

10.   Aura (13 000 searches) – the vibe someone gives off. When used by tweens and teens it is likely a reference to how badass someone is. Aura points make you cooler. So you definitely want to earn more aura points instead of losing them.

We can compare this list with Randoh’s equivalent for the USA, used in the Newsweek article posted previously to which I contributed, and reproduced here with his explanatory comments…

Analysis of Google search data for 2024 reveals the most searched for slang words in America:

1.      Demure (260 000 searches) – reserved, modest or shy in manner or appearance. The TikTok user Jools Lebron made a series of viral videos using the phrase “very demure”. This trend gave the word a playful slang meaning. She uses it to assess appropriate makeup and fashion choices in various settings.

2.      Sigma (220 000 searches) – refers to an independent, self-reliant person who operates outside traditional social hierarchies, often described as a ‘lone wolf.’

3.      Skibidi (205 000 searches) – refers to a viral internet trend featuring surreal, animated videos of singing toilets and dancing heads, popularized on platforms like TikTok for its bizarre humor.

4.      Hawk tuah (180 000 searches) – imitative of a spitting sound. The catchphrase originates from a viral street interview conducted in June 2024 with Haliey Welch, who stated that her signature move for making a man ‘go crazy’ in bed was to ‘give him that hawk tuah and spit on that thang’.

5.      Sobriquet (105 000 searches) – a nickname or descriptive name given to a person or thing. Borrowed from French sobriquet (nickname).

6.      Schmaltz (65 000 searches) – refers to excessive sentimentality or melodrama. Often used for art, movies, music or storytelling if there is too much sappiness.

7.      Sen (50 000 searches) – slang for self.

8.      Katz (34 000 searches) – a term for anything enjoyable, fun or pleasing. It can also mean ‘yes’.

9.      Oeuvre (25 000 searches) – refers to the complete works produced by an artist, writer or composer. A word used by literature professors to express superiority.

10.   Preen (20 000 searches) – slang for a child who tries to act like a teenager(wears teen clothes or makeup).

A spokesperson for Unscramblerer.com commented on the findings: “The English language is ever changing. Every year new slang words are created. Many slang words are born through trending topics and viral videos on social media. However only few manage to stick around long enough to be added to the dictionary and remain in daily use. Slang words are a normal and fun evolution of language. We encourage everyone to learn some new words and surprise their children by using them.”

Research was conducted by word-finding experts at Unscramblerer.com.

We analyzed 01.01.2024 -25.10.2024 search data from Google Trends for terms related to slang words.

Methodology: We used Google Trends to discover the top trending slang terms and Ahrefs to find the number of searches. Americas most popular slang terms can be discovered in Google Trends through the keyword ‘meaning’. People will hear or read slang terms and search for the meaning of the term (example ‘demure meaning’). Ahrefs shows many variations of meaning searches like ‘slang’ or ‘trend’ (example ‘demure slang’) and similar keyword combinations (example ‘what does demure mean’). We added up 150 search variations of top slang terms.

A few days after Randoh’s findings were published, I was asked by Robert Milazzo* to take part in the masterclass on new slang and youth language that he convened at Virginia Commonwealth University. The whole lively one-hour event was recorded and can be accessed here…

https://drive.google.com/file/d/1yYlV7LkKdEf5AqFF-bJQAfIE5s5PUpGi/view?usp=sharing

Robert’s class was particularly illuminating, allowing as it did for contributions from young slang users themselves and from puzzled old-timers too. Bear in mind that the samples handled by data analysts are taken solely from online usage and not from authentic speech. Nearly all the slang used on TikTok, YouTube, Instagram, etc. originates in the USA whereas the slang terms used by British youth in their IRL conversations will differ considerably from their North American counterparts, showing much greater influence from African Caribbean rather than African American sources.

*https://www.linkedin.com/in/robert-milazzo-3a8860116/

THE DISCOURSE OF DIVISION

The US election campaign through a language lens

As the campaigning reached its climax and the polling-stations began to open, I spoke to Kate O’Connell and Gemma Chatwin of the Corporate Communications Team at King’s College London about the language used by the rival candidates, their aides and their supporters during the twelve months since the election process began. Kate and Gemma’s questions are below with my replies…

  • As a language specialist, what have you observed/found interesting about the US election?

One thing that strikes an outsider – British or European, I suggest – is the different  nature of the vocabulary and rhetoric employed in US campaigning: the seemingly chaotic and unrestrained messaging, pivoting and veering unexpectedly into new areas sometimes, showing a lack of consistency, except in tone (Trump’s particularly). There is actually less reliance on a narrow range of repeated specific keywords, slogans and soundbites than has been the case in UK political campaigning – for Brexit, during the pandemic and in the recent election: (‘Take back control’, ‘Brexit means Brexit’, ‘Eat out to help out’, ‘Stop the Boats’ etc.). The Republicans’ messages have been more consistent in emphasising a few key ‘wedge’ issues while Democrats seemed to take a long time to decide on their priorities in terms of focus.

  • How has the language used by both candidates differed? What does their language tell us about their campaign strategy/ voter base?

Linguists – myself included – have tried to track the formulations (not so much genuinely new language as reworking of familiar tropes) used by each side and measure the frequency with which particular topics and particular trigger-words recur. Donald Trump has employed a vocabulary containing many examples of the language of fear and violence, and much intemperate language throughout: ‘vermin’, ‘criminal migrants’, ‘the enemy from within’, ‘radical left lunatics’, and words evoking existential threats: ‘invaded’, ‘conquered’, ‘occupied’, ‘deportation’ and violence: ‘kill’, ‘death’, ‘blood’, ‘nuclear war’, ‘guns trained on her face’. One analysis concluded that Trump had used more violent language than any other recent political orator except Fidel Castro!

Trump has consistently favoured the use of ‘I’ and ‘they’, Harris more often emphasising ‘we’. The Democrats on the other hand, while perhaps favouring less inflammatory language have possibly failed, until the closing days of the campaign (‘neighbors not enemies’ is a last-minute exception), to find memorable, resonant phrases to inspire and motivate. While initially hesitant, and despite Kamala Harris being accused in the more distant past of ‘word salads’ the Democrats, apart from Joe Biden, have been measurably more coherent, while many of Trump’s recent performances have been criticised as meandering if not incomprehensible. His justification for this being that he is practising ‘the weave’, a sort of improvisational incantation that his followers appreciate.

  • We have seen a lot of name-calling in the 2024 election, has it been effective?

A famous example of a slur which seems to have worked is Tim Walz’s characterising of Trump and the Republicans as ‘weird’. This is effective since the word is not especially offensive or toxic but frames the opposition as odd, eccentric, unstable in worrying ways, by implication disturbing – a relatively casual criticism of a community that is old and out of touch with reality. The Republicans accusing ‘immigrants’ of eating pet dogs and cats and likening Puerto Rico to a ‘floating island of garbage’ outraged their opponents, though Joe Biden also came unstuck when he reached for the same metaphor. It’s notable that both sides have used proxies to deliver some of the most stinging criticisms of the leaders, rather than have them delivered by the candidates themselves: ‘childless cat lady’ for example, or ‘unhinged, unstable, unchecked’ – words supplied by former Trump aides and reposted by the Democrats. One rather surprising blip in the unfolding news cycle occurred when Harris suddenly approved the f-word, agreeing when it was suggested to her that Donald Trump was a ‘fascist’. He quickly returned the insult, adding the ‘N-word’ which everyone had so far avoided: ‘I’m the opposite of a Nazi’. Both sides seem to have tacitly put those words aside for the final phase of the campaigning, though tellingly, in a final peroration J.D Vance urged followers to ‘take out the trash’ in reference to the Vice-President.

I think that outsiders listening in bemusement or horror at the campaign rhetoric misunderstand the nature of the voter bases involved. Doom-laden warnings and threats and angry braggadocio can be effective, reassuring and motivating to an audience for whom ‘make America great again’ carries a conviction that the country is at the mercy of hostile forces and on the edge of social breakdown. Conversely Kamala Harris’s more upbeat, feelgood emphasis attempts to instil a cheerful positivity which may not always have been backed up with hard facts or firm commitments (apart perhaps where reproductive rights are concerned).

  • Could this be the first election won on TikTok?

Kamala Harris’s folksy reference, early in the campaign, to having ‘fallen out of the coconut tree’ cleverly appealed to a family audience and referenced her own potentially controversial heritage in a positive way. She has also tried, seemingly with some success, to tap into the female and feminine constituency and the relatively youthful energy  displayed by users of TikTok, a platform which avoids threats and displays of anger and relies on self-promotion, performances of success and – crucially – an element of self-mockery and humour that is entirely missing from Donald Trump’s repertoire. TikTok currently occupies the high-ground of the social media landscape and is a valuable channel by which to reach millennials and GenZ (the latter voting for the first time) millions of whom are potential democrat supporters. It does not reach, however the middle-aged or elderly undecided. Celebrity endorsements apparently can motivate potential non-voters to change their minds and vote, but unsurprisingly probably only affect a demographic which is already on-side anyway (‘Swifties’ for example who are said to have added 400,000 votes to Harris’s tally). Elon Musk’s embracing of Donald Trump is more difficult to assess, as Musk’s own fanbase – tech bros, startup promoters and bitcoin traders among them – aren’t necessarily effective multipliers or influencers on his behalf or Trump’s and perhaps less likely to sway the undecided.

  • How did brat summer and ‘vibes’ benefit Kamala Harris’s campaign?

When pop icon Charli XCX posted her endorsement on X, ‘Kamala IS brat’, young women flooded social media with pro-Harris ‘brat’ memes, kickstarting her takeover from Biden and effectively labelling her as endearingly ‘messy, honest and volatile.’ The democrat campaign switched up to make good use of the tropes and tendencies of pop culture and entertainment media, receiving endorsements from many musicians and Hollywood names, culminating in their candidate’s surprise appearance on Saturday Night Live in which she launched viral versions of her own name -‘End the drama-la’, ‘Cool new step mom-ala’ and returned to that conflicted keyword, asserting that she would be able to open the ‘doors of the garbage truck’ that Trump had fumbled with. This confident banter in the very last moments of the campaign, along with her pivot, after Bill Clinton’s disastrous intervention, to promising some sort of support for Gaza, can only help the democrats’ chances, and these messages are featuring in places that Trump cannot usually access. Nevertheless the Republican candidate is doubling down on his insurrectionist rhetoric, welcomed by his base, saying now that he ‘should never have left the White House in the first place’.

My friend Serena Smith wrote perceptively for Dazed magazine about the role of celebrities in the presidential race…

https://www.dazeddigital.com/life-culture/article/64995/1/will-pop-culture-impact-the-result-of-the-2024-us-election

Once the race was over the avalanche of post-mortems and recriminations began. Among them were a few which focused, as I had tried to, on the discourse of division. In the New Yorker Joshua Rothman considered the very different flavour of the two parties’ language…

“Id been spending a lot of time watching interviews with Kamala Harris and Donald Trump – conversations that tended to be below average. On shows like “60 Minutes” and in her CNN town tall, Harris had been charming and trenchant but also repetitive and inflexible. Restrained by her determination to stay on message, she often failed to answer questions directly. Trump, for his part, lied, rambled and spouted nonsense as usual. And yet his lack of constraint at least made him entertaining…

…Harris and Trump’s flawed performances were typical of the duelling communications styles now wielded by Democrats and Republicans. Broadly, Democrats preach while Republicans riff; Democrats stick to their messages while Republicans let loose with whatever comes into their heads.”

In the Guardian Nesrine Malik convincingly dismantled the lazy consensus that held that the result was a defeat for the Democrats’ supposedly embracing ‘woke’ policies and relying on endorsement by ‘woke’ celebrities…

https://www.theguardian.com/commentisfree/2024/nov/25/woke-lost-us-election-patrician-class-identity-politics