If you enter a product name into Google followed by “reddit,” the search engine delivers human opinions rather than affiliate pages. The reason is that Reddit users share their views without any sales incentive pushing them. Yet the question arises: what happens when a brand decides it wants access to those same opinions?
A Reddit scraper has uncovered a group of accounts that drive brand mentions in buying threads, with a small number of users accounting for an outsized portion of the posts. The evidence points to these posters acting like paid shills rather than casual fans.
The Reddit Hack and Why It Works
Dmitri Brereton’s essay on Google search pointed to the same practice, which dates back to 2022, when Mike Riggs wrote about it in Reason. He noted that a query ending with “reddit” brings up human responses rather than affiliate pages. The wager at the heart of the habit is that someone posting in r/chefknives has no motive to deceive you about a knife.
The wager has a clear weakness: if Reddit is where people go for free advice, then Reddit is also where brands would hope to place paid advice. The researcher was curious whether the knife subreddits he follows, and scrapes for New Knife Day, display any such signs. He did not want a suspicion about a single suspicious remark, but something he could measure and which another person could check again.
GLiNER and the Corpus Problem
A named-entity model known as GLiNER was fine-tuned by the researcher to extract brands, models and steels from knife comments. It pulls out Mazaki as a brand, Fibrox as a model and white #2 as a steel, per “picked up a Mazaki in white #2, way better than my old Fibrox”. The model then runs across every comment gathered by the New Knife Day scraper from six subreddits: r/knives, r/knifeclub, r/chefknives, r/japaneseknives, r/FixedBladeEdc and r/KnifeSteels.
He already knows who wrote every comment, which brands each one names, and whether the thread it sits in is someone asking what to buy. So a narrow question can be asked instead: in the threads where a recommendation changes a purchase, who is doing the recommending?
What Paid Posting Leaves Behind
Nobody publishes their shill accounts, so the researcher had to decide in advance what paid posting would leave behind. The market for it is not hidden. REDCmts sells one Reddit comment for $9.99 and 100 for $699.99, from what it calls “real, aged accounts”, and shows a gallery of brand mentions it says it delivered. Soar says its accounts are “aged and manually warmed” for weeks before a single brand mention. Bazzly advertises automated replies to every post that looks like someone shopping.
If we treat those sales pages as the product’s own description, then a paid campaign for a single brand, run across a small set of prepared accounts, would appear as such.
- A small tail of accounts writing a disproportionate share of the brand mentions in “what should I buy” threads.
- Those accounts naming one brand almost every time they name any.
- Thin accounts: few comments, low scores, no real standing in the subreddit.
- Young accounts, or accounts with histories that are hidden or wiped.
- Accounts that post mostly in knife subreddits, since the knife comments are what is being paid for.
- Links to a store or an affiliate page.
Each one of those matches the kind of post a dedicated fan, or the maker’s employee posting on their own time, or a brand’s own subreddit regulars entering a buying thread, would make on their own. Data from public Reddit shows that recommendations cluster together, though it offers no explanation for why they do so.
The Refresh That Changed the Answer
Each new post and its comments get stored shortly after posting by the scraper. The problem is that the wrong moment was chosen for this particular question: a buying thread gathers its recommendations over the following day or two, and r/knives posts had 1.5 stored comments each. To correct it, a refresh pass went back to 3,607 posts older than 48 hours and refetched their comment trees, increasing the corpus from 21,673 comments to 51,129.
The test came up empty before the refresh, since roughly 800 buying-thread references were too scarce to distinguish 7.6% from the random 7.1% chance.
There are three terms worth defining here. A buying thread is a post whose title or body matches phrases like “should I buy”, “recommend”, “under $” or “best knife”; it relies on a regular expression rather than a classifier to identify it. Brand-heaviness for an author is the portion of their comments that name a brand, weighted so that naming the same brand repeatedly carries more weight. The tail refers to the top 5% of the 987 authors who have posted 10 or more comments, measured by that score, and includes 49 accounts. He uses this scoring approach because an account that keeps returning to the same brand is the very product that the vendors above are trying to sell.
The Numbers That Raised the Alarm
The problem is figuring out what portion of buying-thread mentions the tail would produce purely by chance, considering how much everyone posts. To find that figure, he preserves every brand mention where it sits, within its thread and tied to its brand, while scrambling the author names across those mentions instead, like mixing up name tags. A prolific account still ends up with many mentions and a quiet one with few, but which threads an account shows up in is no longer tied to who that account is. He repeats this process 1,000 times and logs the tail’s portion each run.
When the tail appears in purchasing discussions simply because it posts frequently, random assignment would expect it to contribute to roughly 7.9% of the mentions of the brand there, and nearly always within the range of 6.3% to 10.1%. Instead, it wrote 11.3%. Just 2 out of the 1,000 random assignments managed to hit that mark.
“Only 2 of the 1,000 random reassignments reached that.”
About one out of every nine buying-thread recommendations stems from these 49 accounts, when counted plainly.
What This Means for Knife Buyers
New Knife Day is the researcher’s site that documents knives and steels and follows which blades Reddit users are acquiring and debating. He stands to gain from knife Reddit remaining relevant. The evidence hints his interest might no longer be secure.
That an account writes a large share of mentions of a brand within buying threads, far beyond what chance would allow, does not prove payment for posts. Such a pattern fits with paid posting. The same pattern also fits with devoted fans, with employees posting on their own time, or with regulars from the brand’s own subreddit.
The researcher’s own admission carries weight. He points out that public Reddit data can reveal that recommendations are concentrated, but it cannot explain why. The data backs up a finding, not a conclusion.
The figures support an observation, not a final statement. The investigator has completed the calculations and put forward the inquiry. Whether the needle was placed there or found by chance remains unknown to the data itself. Still, the numbers pose the question, and they do so with real weight.
Source material: “Does Reddit have an astroturfing problem? What the data suggests,” petervijeh.com.
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