Ever found yourself scrolling through TikTok or YouTube comments and feeling like you’ve stumbled into a conversation in a foreign language? You see words like seggs, unalive, or references to a “spicy accountant”, and you get the distinct impression you’re missing something crucial. You’re not just out of the loop on a new meme; you’re witnessing a fascinating linguistic phenomenon in real-time: algospeak.
Algospeak is the internet’s rapidly evolving cryptolect, a shared code language designed for one primary purpose: to evade the watchful eyes of automated content moderation systems. It’s a digital cat-and-mouse game where human creativity is pitted against machine learning, and the result is a vibrant, chaotic, and sometimes confusing new dialect.
The Birth of a Necessary Code
To understand algospeak, you first have to understand its adversary: the algorithm. Platforms like TikTok, YouTube, Instagram, and Facebook employ sophisticated AI to scan content—videos, captions, comments, and audio—for keywords and topics that violate their community guidelines. These topics often include:
- Sexuality and nudity
- Violence and self-harm
- Hate speech
- Harassment and bullying
- Misinformation (especially concerning health or politics)
The problem is that these algorithms are powerful but notoriously clumsy. They lack the human ability to understand context. They can’t easily distinguish between someone promoting violence and someone discussing a historical event, or between sexual solicitation and a frank conversation about sexual health. For creators, posting about these “forbidden” topics, even in a responsible or educational way, can lead to a video being taken down, demonetized, or “shadowbanned”—where its visibility is secretly restricted without notifying the user.
Faced with this digital censorship, users did what humans do best: they adapted. Algospeak was born out of the necessity to discuss sensitive or controversial subjects without triggering the algorithmic tripwires. It’s a workaround that allows communities to continue their conversations, just under a thin veil of code.
The Linguistic Toolkit of Algospeak
What makes algospeak so fascinating from a linguistic perspective is the variety of creative strategies users employ. These aren’t random; they follow predictable patterns, many of which are modern updates to older forms of internet slang like Leetspeak (1337sp34k).
1. Phonetic & Sound-Alike Substitutions
This is perhaps the most common technique, replacing a flagged word with a new one that sounds similar when spoken aloud. The new word is often nonsensical or comical, which adds to its appeal.
- seggs (or seggsy) → sex
- leg booty → LGBTQ+
- corn → porn (originating from a meme, this one is layered)
- vibranium → vibrator
2. Orthographic & Visual Substitutions
This method involves altering the spelling of a word to fool text-scanning AI while keeping it readable for humans. It’s a direct descendant of Leetspeak, where letters are replaced with numbers or symbols.
- unalive → kill, die, suicide (This is one of the most widespread examples, used to discuss everything from true crime to mental health.)
- le$bian, l€sbian → lesbian
- p@ndemic, panny-d → pandemic
- v!olence → violence
- Using letters from other alphabets, like the Cyrillic ‘а‘ for the Latin ‘a‘, which look identical but are different characters to a computer.
3. Semantic Substitutions & Euphemisms
This is where algospeak gets truly creative. Users replace a flagged word with a completely different, often unrelated, word that has been culturally agreed upon as a stand-in. These are true code words that require in-group knowledge.
- accountant → sex worker (This emerged from a trend where sex workers would humorously describe their job in corporate terms to avoid censorship.)
- mascara → used in a very specific context to refer to sexual assault, stemming from a trend where users shared stories of trauma using mascara as a metaphor for a bad experience (“I tried to give my mascara to him but he stole it”.)
- spicy → can refer to anything from sexy or explicit content to neurodivergence (e.g., “neurospicy”).
- camping → used to refer to abortion, particularly after the overturning of Roe v. Wade in the United States, as a code for people seeking or offering help to travel out of state.
More Than Just Dodging Bots: The Cultural Impact
While algospeak’s primary function is technical avoidance, it has evolved to have a much deeper cultural significance. It functions as a shibboleth—a linguistic password that signals you belong to a particular online community. Knowing that “panini” means “pandemic” or that someone is talking about their “accountant” means you’re “chronically online” enough to be in on the joke. It fosters a sense of solidarity and shared identity among users navigating the same restrictive digital spaces.
However, this coded language isn’t without its downsides. There are two major concerns:
- Inaccessibility and Obfuscation: The very nature of algospeak means that crucial information can be hidden from those who need it most. Someone genuinely searching for help or resources on suicide or sexual assault won’t know to search for “unalive” or “mascara”. The code that protects the creator can become a barrier for the vulnerable audience member.
- Trivialization of Serious Topics: Discussing suicide as “unaliving yourself” or sexual assault through a metaphor about makeup can create an emotional distance from the gravity of the subject. While this coping mechanism can be helpful for some, critics argue it can also sanitize and trivialize deeply serious issues, making it harder to have nuanced and direct conversations.
An Ever-Evolving Digital Dialect
Algospeak is not a static language. It is in a constant state of flux. As soon as algorithms “learn” to flag a new term like seggs, the community moves on to the next iteration. It is a living, breathing testament to human linguistic ingenuity under pressure. The constraints imposed by technology have, paradoxically, become a catalyst for immense creativity.
This phenomenon forces us to ask big questions about the future of online discourse. How do we balance platform safety with the freedom to discuss difficult topics? Can AI ever truly understand the nuances of human language? As long as our online spaces are moderated by unfeeling and context-deaf algorithms, users will continue to play the game. They will invent, adapt, and code their language, ensuring that no matter the rules, the conversation will go on.