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THEY’RE BRAINWASHING YOU! (& other secrets that made you click) - Etymology Nerd

Adam Aleksic is a linguist, content creator, and author, best known online as the Etymology Nerd. What’s happening to language right now? Words like “rizz” and “skibidi” can make it feel like you’re out of the loop, but are you actually getting older, or has the internet transformed language into something entirely new? What does the science of linguistics say about this shift? Expect to learn why 6-7 was voted word of the year for 2025, why TikTok is becoming the most powerful linguistic engine on Earth, if there is a science to meme language, why funny language spreads and what makes it stick, why we should care about linguistics, and much more… - 0:00 The Truth Behind “Word of the Year” 2:31 Is TikTok Rewiring How We Speak? 3:27 Do Social Platforms Create Their Own Dialects? 5:34 The Hidden Formula Behind Influencer Language 13:47 Why MrBeast Changes His Voice 17:01 Internet Subcultures and Their Unique Languages 18:33 How Newscasters Engineered Their Signature Voice 21:12 Why Sports Commentators Sound So Distinct 22:38 Is Distribution Is the Key to Going Viral? 26:44 Can You Hear Sexuality in Someone’s Voice? 33:38 Are Lesbian Accents Hard to Identify? 40:32 Should We Replace Words With Emojis? 43:37 The Surprising Evolution of Etymology 45:26 Are Young People Driving Language Change? 47:10 Why We Reject Forced Language 48:34 Where Do Filler Words Come From? 52:14 The Most Powerful Language Tricks Creators Use 54:58 How AI is Changing the Way We Speak 01:02:55 Can One Word Capture a Whole Idea? 01:04:17 Social Media vs AI: What’s Worse For Language Development? 01:08:20 How Language Shapes the Way We Think 01:10:41 What It Really Means to Be Gen Z 01:14:40 Why Teenagers Naturally Rebel 01:20:20 Rapid-Fire: The Origins of Everyday Words 01:24:37 The Power of Creating Your Own Language 01:28:21 Was QWERTY Designed to Be Inefficient? 01:31:57 Does ChatGPT Actually Speak English? 01:33:49 Is Language Evolving Faster Than Ever? 01:35:02 Where to Find Adam - Get 10% discount on all Gymshark products at https://gym.sh/modernwisdom (use code MODERNWISDOM10) Get 35% off your first subscription on the best supplements from Momentous at https://livemomentous.com/modernwisdom Sign up for a one-dollar-per-month trial period from Shopify at https://shopify.com/modernwisdom Get 15% off your first order of my favourite Non-Alcoholic Brew at https://athleticbrewing.com/modernwisdom - Get access to every episode 10 hours before YouTube by subscribing for free on Spotify - https://spoti.fi/2LSimPn or Apple Podcasts - https://apple.co/2MNqIgw Get my free Reading List of 100 life-changing books here - https://chriswillx.com/books/ Try my productivity energy drink Neutonic here - https://neutonic.com/modernwisdom - Get in touch in the comments below or head to... Instagram: https://www.instagram.com/chriswillx Twitter: https://www.twitter.com/chriswillx Email: https://chriswillx.com/contact/

Chris WilliamsonhostAdam Aleksicguest
Apr 18, 20261h 35mWatch on YouTube ↗

CHAPTERS

  1. 0:00 – 2:31

    “Word of the Year” as virality marketing: ‘six seven’, rage bait, and meta-meaning

    Chris and Adam unpack why dictionaries’ “Word of the Year” choices often function as marketing and distribution plays rather than purely linguistic milestones. Adam argues that even seemingly meaningless viral tokens like “six seven” carry meaning as a critique of the attention economy and clip culture.

    • “Big dictionary” incentives: controversy and visibility over linguistic merit
    • ‘Six seven’ as a self-referential meme designed for clipping and sharing
    • Absurdity itself as meaning; “meta words” and knowing winks to the algorithm
    • Rage bait and “slop/brain rot” as labels reflecting platform anxieties
  2. 2:31 – 3:25

    TikTok as a linguistic engine: accelerated slang cycles and algorithm-shaped conversation

    Adam makes the case that TikTok (and adjacent platforms) now drive a large share of slang creation and diffusion. The UI, algorithmic feedback loops, and “conversation-first” culture compress the time from invention to mainstream adoption.

    • Platform origin shifts: from 4chan/Reddit/Twitter toward TikTok + Twitter/X
    • Language innovation as a byproduct of interface and comment-driven participation
    • Echo chambers and trend mechanics accelerate slang churn
    • Algorithmic amplification reshapes what gets repeated and remembered
  3. 3:25 – 4:20

    Platform dialects and micro-dialects: LinkedIn vs Twitter vs fandom language

    They explore how different platforms operate like different “rooms,” producing distinct expectations for tone, vocabulary, and identity signaling. Adam emphasizes that even within a single platform, communities form micro-dialects with their own norms.

    • Platform as “house”: situational register and audience expectations
    • LinkedIn professionalism vs Twitter play vs TikTok fandom-speak
    • Micro-dialects: K-pop, Swifties, niche subcultures inside the same app
    • Language as a badge of in-group membership
  4. 4:20 – 5:34

    Keyword virality and in-group signaling: ‘jester maxing’ and the algorithm’s bait words

    A viral ‘incel/manosphere’ phrase becomes a case study in how keywords act as distribution triggers and identity markers. Adam argues these phrases often function less as literal propositions and more as algorithm-aware signals that invite clipping and outrage.

    • Viral jargon as “knowing wink” to the recommendation system
    • Keywords as algorithmic accelerants: “maxing,” “gooning,” etc.
    • Harmless vs harmful virality; diffusion can normalize toxic frames
    • Slang as identity: proving you’re part of the cohort
  5. 5:34 – 9:23

    The influencer voice blueprint: founder effects, ‘vibe theft’ lawsuits, and speech optimized for retention

    Adam breaks down the “influencer accent” and recounts consulting on a lawsuit about copying an influencer’s vibe—including vocal style. They connect modern influencer speech patterns to a lineage of founders (Kim K, early YouTube beauty creators) and algorithmic incentives like retention and floor-holding.

    • Case study: influencer lawsuit where accent/style was part of the claim
    • Linguistic founder effect: copying successful early movers
    • Lifestyle influencer accent traits: softness, relatability signals, uptalk/vocal fry
    • Retention mechanics: dragging syllables, avoiding silence, ‘floor holding’
  6. 9:23 – 13:57

    Educational authority vs lifestyle coziness: diction, consonants, and the pressure to homogenize accents

    Chris and Adam compare ‘educational influencer’ speech to lifestyle influencer speech, then zoom into diction and accent modification. They discuss how online norms push creators toward standardized, “legible” accents—often at the cost of regional identity and perceived status.

    • Educational influencer voice: pace, stress patterns, authority cues
    • Diction mechanics: consonants as structure, vowels as color; glottal stops
    • Algorithm as a bottleneck: favors widely recognizable pronunciations
    • Code-switching pressure for non-prestige accents (e.g., Indian creators)
  7. 13:57 – 17:02

    MrBeast, livestream ‘edging,’ and the craft of delaying payoff to prevent scrolling

    They analyze MrBeast’s heightened on-camera voice as an engineered attention device, distinct from his interview voice. The conversation expands into livestream dynamics, where perpetual anticipation and delayed gratification keep viewers from leaving.

    • MrBeast voice as deliberate attention-maximization for younger audiences
    • Shock-and-awe cadence: constant excitement to suppress scroll impulses
    • Livestreams as unbounded ‘payoff delay’ machines (permanent anticipation)
    • Parallel between visual clickbait and auditory/linguistic clickbait
  8. 17:02 – 23:18

    Subculture language factories: 4chan selection pressure, manosphere diffusion, and broadcaster voices

    Adam explains why 4chan became a powerful slang incubator: anonymity forces rapid in-group verification through language. They connect this to broader “media voices” like newscaster and sports commentator styles—professionalized registers shaped by institutional expectations and founder effects.

    • 4chan anonymity drives selection pressure for insider slang proficiency
    • Manosphere lexicon diffusion into Gen Z slang (pilled, maxing, etc.)
    • Newscaster voice as authority performance; standardized broadcast accents
    • Sports commentary as excitement-performance—closer to entertainment registers
  9. 23:18 – 26:40

    Distribution beats content: TED Talk cadence, outrage-optimized virality, and why ‘warm & fuzzy’ loses

    They argue that modern media rewards distribution and emotional arousal over message quality. Adam describes a structural misalignment where anger/awe/humor spread, while contentment and true wellness underperform—leading creators to ‘perform’ wellness rather than embody it.

    • TED Talk as declining format; clip-farming as the new distribution strategy
    • Virality rewards arousal emotions (anger, fear, awe) over calm contentment
    • “Like” as willingness-to-click, not actual liking
    • Wellness content as aestheticized performance shaped by platform incentives
  10. 26:40 – 40:16

    Can you hear sexuality? Gay/lesbian speech research, Polari, and language as identity under power

    Adam discusses research on ‘gay accent’ perception and the more mixed evidence around ‘lesbian accents.’ They broaden into how marginalized groups develop slang and cants (like Polari) for signaling and safety, tying language to power and social subversion.

    • Perceived ‘gay accent’ features and identity signaling (non-monolithic)
    • Lesbian accent research: mixed findings; caution against reductionism
    • Polari and other queer cants as evasion + in-group signaling tools
    • Slang pipelines: AAE → queer communities → mainstream diffusion
  11. 40:16 – 43:37

    Emojis as language: substitution, tone tags, and why courts struggle with shifting meaning

    They treat emojis as legitimate linguistic units with multiple roles: replacing words to evade moderation, adding emotional context, or functioning as standalone reactions. Real court cases illustrate how unstable emoji semantics can be and why context is essential for interpretation.

    • Emoji functions: word substitution (censorship), paralanguage/tone tagging, reactions
    • Canadian thumbs-up case: does it legally confirm a contract?
    • Emoji meanings drift quickly (crying/laughing/irony cycles)
    • Ambiguity without intonation makes context and precedent crucial
  12. 43:37 – 51:38

    Etymology as a mirror of reality: semantic drift, young innovators, and resistance to forced language

    Adam reframes etymology as less about linear ‘progress’ and more about changing human realities and identities. They discuss how young people drive slang adoption, while institutions tend to legitimize rather than successfully impose vocabulary—especially when words feel forced.

    • Etymology’s role: language reflects changing lived reality (what we notice/need)
    • Word shortening, portmanteaus, and ongoing semantic recombination
    • Youth as primary slang engine (roughly ages 10–25)
    • Top-down language imposition often backfires (‘fetch’ problem); institutions ratify later
  13. 51:38 – 54:58

    Creator language mechanics: hooks (‘No, because…’), filler words, and ‘all words are keywords’ now

    They dissect how creators hook attention using in-medias-res openings and conversational “turn-taking” devices. Adam argues the algorithmic era turns ordinary language into metadata, where every word can influence distribution and audience interpretation.

    • Hook formats that mimic mid-conversation entry (‘No, because…’)
    • Filler words as floor-holding and turn-taking signals; stigma vs function
    • “All words are keywords”: speech as SEO/metadata for recommendation systems
    • Multi-layer signaling: to the algorithm and to the viewer simultaneously
  14. 54:58 – 1:04:16

    AI’s linguistic fingerprints: ‘delve,’ Latin prestige bias, and humans being trained by models

    Adam explains how LLM training and reinforcement processes can bias output toward certain prestige words and structures, which then feed back into human writing and speech. They discuss detectable markers (delve, em dashes) and the deeper concern: subtle shifts that normalize AI-shaped discourse.

    • Empirical spike: ‘delve’ usage rising post-ChatGPT; model overuse vs humans
    • Reinforcement and prestige effects: Latin-derived vocabulary favored over Germanic
    • Counter-signaling emerges (avoiding ‘delve,’ avoiding em dash patterns)
    • Bigger worry than word choice: bias and worldview shaping through AI-mediated text
  15. 1:04:16 – 1:35:43

    Language, thought, and the future: Overton windows, AlgoSpeak workarounds, extinction, and ‘Gen Z’ as a label

    They close by zooming out: social media as the bigger threat than AI due to speed and network amplification, plus the way discourse shifts Overton windows. Adam argues humans will invent workarounds (AlgoSpeak) but warns about homogenization, language extinction, and identity labels like ‘Gen Z’ acting as constraints.

    • Social media vs AI: social platforms amplify and weaponize diffusion fastest
    • Linguistic relativism and ‘1984’ vs ‘Brave New World’ framing
    • AlgoSpeak: censorship produces creative linguistic mutations, but with costs
    • Language extinction and lost conceptual affordances; labels (Gen Z) as commodifying buckets

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