The same week, two reports land on your desk, both backed by hard numbers. One says Reddit is the single biggest source of AI citations, at 40.1% across the major engines. The other, a University of Toronto study, says AI search almost never cites social platforms — 0% in some verticals. Neither is bluffing; you can go check both yourself. The problem is they read like descriptions of two different universes, and you’re about to budget next month around one of them.

Here’s the verdict up front: both are correct. They only clash when you skip one question — which stretch of road each one measured. And reading 40% as “go open a few accounts and seed Reddit and PTT” is the most expensive misreading these two numbers can produce.

40 vs 0 Isn’t a Math Error

Put both hands on the table first.

Semrush analyzed 150,000 citations across the major LLMs in June 2025. Reddit came first at 40.1%, with Wikipedia and YouTube close behind (we cited this in the off-site authority piece). Read that table alone and the conclusion is intuitive: AI loves real human discussion, and social is the main battlefield.

On the other side, a large University of Toronto empirical study from September 2025 (arXiv:2509.08919) put AI search and traditional Google side by side. Take Canadian automotive queries: in Google’s cited sources, social makes up 22.8%; in AI search, that cell is 0% — earned media (third-party reviews, news) takes 69.1%, and the rest goes to brand-owned content. The paper’s summary word for social is “near-total exclusion.” And it isn’t uniform: Claude and ChatGPT are the most conservative and barely touch social, Perplexity is the most permissive, and Gemini sits in the middle.

40% versus 0%. A gap that size usually isn’t a dragged Excel formula — it’s two rulers measuring completely different stretches of road. Here’s where the rulers differ.

The Caliber Lens: Four Questions That Let 40% and 0% Both Hold

The same brand can be “40% of AI citations are social” and “0% social in AI answers” at once, as long as you separate four things. Those four things are the caliber you should read off before trusting any GEO number.

1. Which kind of query did it measure?

Semrush’s 150,000 citations are a grab bag across query types, stuffed with informational, how-to, and troubleshooting questions. “How do I configure product X,” “what causes symptom Y” — that’s exactly where Reddit’s sprawling many-voices threads naturally surface.

Toronto didn’t measure that. It targeted decision-stage queries in verticals — “recommend a good X,” the kind you ask while choosing a brand or a vendor. And the same paper found that consideration-stage queries are dominated by earned media, while transactional queries push every engine toward brand-owned content. Social gets squeezed to the margin in both.

Verdict: the two rulers cover two different intersections of your customer’s journey. The 40% lives in “I hit a problem and went looking for an answer” — the informational long tail. The 0% lives in “I need to pick a vendor” — the decision point. And the decision point is the one that decides whether you get the business. In the questions your customers type right before they open their wallet, social barely counts.

2. Which engine did it ask?

“AI citations” was never one number. In Toronto’s data, Claude and ChatGPT keep social locked outside the door, Perplexity waves it through, and Gemini lands between them. On that one cell alone, the four engines’ policies span from “near zero” to “fairly welcoming.”

Semrush’s 40.1% is a weighted average that blends those engines together. Using a cross-engine average to predict one engine’s behavior is like using the class average to guess how one student scored. If your customers mostly ask Claude, that 40% means almost nothing for you; if they ask Perplexity, it’s worth a glance.

Verdict: an “AI citation share” with no engine attached carries less information than you think. Find out which engine your customers actually use before you decide whether that number is yours.

3. Which moment did it measure?

The citation map reshuffles constantly; it’s not a stable atlas. We logged one example in the off-site authority piece: Reddit’s citation share inside ChatGPT fell from 60% to 10% over two months, simply because OpenAI changed its retrieval parameters. Toronto’s fieldwork closes in September 2025; Semrush’s snapshot is June 2025 — and the months in between were exactly a stretch of violent swings in the social share.

Verdict: a GEO citation number with no date is as useless as a stock screenshot with no date. 40.1% is a reading from one specific month under one specific engine mix — not a physical constant.

4. What did it count as “one citation”?

This is the easiest question to skip and the most decisive. Semrush counts “this domain appeared in the citation list” — appear once, log one. But “made the list” and “actually held up that answer” are two different things.

A separate 2026 empirical study (arXiv:2604.25707) splits this into two layers: citation selection (did the platform pull you into its source list) and citation absorption (once pulled in, did you actually contribute the answer’s language, evidence, and conclusions). It found that news sources get “selected” often but absorbed far more shallowly than encyclopedic sources — being on the list isn’t the same as being heard. The same study found that Perplexity, which casts the widest net, averages 16 sources per answer but the lowest influence per source; ChatGPT cites the fewest and has the highest influence per page.

Stack those two facts onto Reddit: a wide-net engine hangs a long string of links to hit its source quota, and Reddit is easily a few of them — which inflates its share of the citation list without meaning it shaped the answer. Which is to say, even that 40.1% may overstate Reddit’s real effect on what AI actually says.

Verdict: “appears in the citation list” is the lowest bar for being cited. What’s worth money is being absorbed — and list share can’t see absorption.

Stack the Four Lenses: AI Trusts Consensus, Not Your Posts

With all four caliber questions answered, 40% and 0% stop fighting. What’s left is a more useful question: when AI does pick up a Reddit thread, what is it actually picking up?

It’s picking up a consensus thread that hundreds of real people pushed up, argued over, and vetted. The mechanism behind that 40% is “lots of independent real people say the same thing, so the claim is credible.” That’s precisely what a paid ghostwriter can’t manufacture — ten accounts praising one brand in similar phrasing over three days isn’t volume to AI, it’s an anomaly signal (we take that mechanism apart in the fake-testimonial and social-spam piece).

The reverse makes it even clearer. The study focused on Google’s family (arXiv:2604.27790) logged an embarrassing case: during a live boxing match, an AI summary declared a winner based on a single satirical Facebook post — and got it wrong. Engines have been burned by thin social content, so they grow more, not less, wary of sparse, single-source, manipulated-looking social signals. The door to social is narrowing and getting more consensus-gated, not swinging wider.

Verdict: reading “Reddit is 40%” as “go astroturf it” is a double misread. Wrong on caliber — that 40% mostly sits in queries your customers won’t type, engines you may not be fighting on, a moment that’s already expired, and it overstates the real effect. Wrong on mechanism — what AI trusts is the mass real-human consensus you can’t fabricate, and the seeded threads you can fabricate are exactly the kind it down-weights. The harder you spam, the more you look like the thing it learned to avoid.

So Should You Touch Social at All?

Don’t swing to the opposite extreme and write social off entirely because of this piece. Perplexity really is more permissive toward social, real discussion still surfaces on informational queries, and PTT and Dcard play a role for the Taiwan market much like Reddit’s in the English-speaking world — they’re the pool of how real people talk about you.

The difference is in how you play it. Social isn’t a placement channel where you buy slots and push content; it’s a judges’ bench you don’t control. What you can do is make the product and service good enough to get discussed by real people on their own, and aggregated by third parties into reviews and coverage — let the consensus grow, instead of forging it. The first is slow, but it’s what that 40% actually rewards. The second is fast, but what it buys is AI remembering “this brand shouldn’t be cited.”

The Lesson Is Worth More Than Either Number

If this piece leaves you with one thing, don’t let it be 40% or 0%. Let it be the four questions.

GEO statistics fly around this field: citation market share, brand mention rate, “platform X owns 80% of AI traffic.” Every one carries a caliber, and swap the caliber and the number can move several-fold — we demonstrated this in the deep analysis of the five engines’ citation mechanics, where the same ChatGPT market share reads 46% in one dataset and 77% in another, purely because one measures app reach and the other measures browser referrals. The number isn’t lying to you; the omitted caliber is.

Verdict: with any GEO number, ask four things first — which query type, which engine, which moment, what counts as one citation. If you can get answers, the number can enter your decision. If you can’t, it’s the same species as the monthly report a vendor can’t reproduce for you: unfalsifiable, and commercially worth zero. Ask the caliber, then decide whether to swallow it.

This Week

  1. Take any “should we invest in platform / channel X” GEO recommendation you’re holding and run it through the four caliber questions. Keep what survives all four; shelve what can’t answer.
  2. Don’t rush to budget for seeding Reddit, PTT, or Dcard. Put that money into assets you actually own and that genuinely get aggregated by third parties — your site’s health, real customer testimonials with identities attached, product facts worth writing into a review. The payback is slow, but only these hold up as engines rewrite themselves month over month.
  3. The hardest part isn’t reading the number — it’s the judgment call. “In my industry, for the queries my customers actually type, on the engines I’m fighting on, does social count?” That answer takes engine-by-engine, query-by-query testing, plus tracking a distribution that reshuffles every month — not something one round of spot-checking can close. Run a free audit on geoweb.tw to see where your health actually sits, then send your brand and the report to [email protected]. We’ll give you a caliber-tagged read from real measurements — including the parts that come back “you don’t need to touch this cell right now.”

Caveat: the Semrush 40.1% figure and the shift in Reddit’s share inside ChatGPT are relayed from industry data compiled in our own off-site authority piece; the academic findings come from arXiv:2509.08919, 2604.25707, and 2604.27790, all checkable. The “selection vs. absorption” gap was measured on news and encyclopedic sources; this piece infers from it that wide-net engines pad Reddit’s list share — a reasonable inference, not a direct measurement of Reddit. There’s no public empirical data on PTT’s or Dcard’s actual share of the AI citation pool.

Further Reading