Reddit astroturfing: what 51,129 knife-forum comments suggest

Peter Vijeh, who runs the knife-collector site New Knife Day, has published an analysis asking whether Reddit's knife communities show the fingerprints of paid posting. His conclusion is deliberately measured: recommendations are more concentrated than chance alone explains, but the accounts responsible look like ordinary enthusiasts, not hired shills.

What he measured

The corpus covers six subreddits: r/knives, r/knifeclub, r/chefknives, r/japaneseknives, r/FixedBladeEdc and r/KnifeSteels. A named-entity model tags brands in every collected comment, and "buying threads" are defined by a regular expression over titles and bodies, matching phrases like "should I buy" or "best knife".

A refresh pass changed the answer. The scraper stores comments too early: buying threads gather advice over the following day or two, so r/knives posts had only 1.5 stored comments each. Refetching 3,607 posts older than 48 hours took the corpus from 21,673 comments to 51,129 across 6,675 posts.

The tail is the top 5% of the 987 authors with at least 10 comments, ranked by how heavily they lean on one brand: 49 accounts. Vijeh then reassigned author names across all brand mentions at random 1,000 times, so each account kept its posting volume but lost any link to the threads it appeared in.

What the numbers show

That shuffle predicts the tail should write about 7.9% of buying-thread brand mentions, almost always between 6.3% and 10.1%. It wrote 11.3%, and only 2 of the 1,000 shuffles reached that: about one recommendation in nine comes from these 49 accounts where chance says one in thirteen, roughly 50 extra mentions out of 1,471.

The concentration is uneven. Two subreddits sit above chance, r/chefknives at 14.9% against 7.7% and r/knifeclub at 12.4% against 7.3%, while r/knives, the largest, stays within half a point of chance. Brand by brand the pattern repeats: a chef's-knife brand coded B003 draws 31.2% of its buying advice from the tail against 8.0% expected, four times chance, and B004 draws 26.1% against 8.2%. The brands are coded, since concentration alone is not evidence that anyone paid.

What the full histories showed

Vijeh also fetched the full Reddit histories of the 23 tail accounts behind the three brands with a signal, plus 23 comparison accounts. Eight tail histories and seven comparison ones were hidden, suspended or deleted. Among the rest, median account age was 4.5 years in both groups. Only 3% of the tail's comments sat in the six knife subreddits against 10% for the comparison group.

Across their whole history the tail named seven knife brands, not one, which Vijeh says is not what a warmed, single-purpose account looks like. He tested eight brands and six subreddits, so a row or two can look odd by luck; neither the buying-thread regex nor the brand tagger was checked against hand-labelled samples; and the study covers six subreddits, not Reddit. His practical suggestion: when an unfamiliar account recommends a knife, check whether it has ever named a different brand.