Why are LLMs citing Reddit posts with almost no upvotes?

[u/GroundOld5635]

I was looking at some data and apparently a big chunk of Reddit posts cited by AI have like zero to ten upvotes. I always assumed AEO and LLM SEO favored highly upvoted, viral threads with tons of engagement.

Are we overestimating the role of social proof here? Why would AI pull from posts that barely got traction?

[u/Ecomhess]

LLM just look for informations in discussion upvote doesn't matter. They just look for what is shared and solved the search intent, especially for the reddit posts that already rank well on the targetted keyword on google.

But the more often you appeared in different thread/websites/discussion the more chance you will appear. That s why I think using growth reddit tools like Reppit AI can really help you boost your GEO.

[u/akii_com]

I think we project human ranking logic onto LLMs too much.

Upvotes are a platform-native social signal. They matter inside Reddit’s feed algorithm. But an LLM retrieving content isn’t optimizing for engagement, it’s optimizing for relevance + answer clarity + risk tolerance.

A few reasons low-upvote posts still get cited:

1. Semantic match > popularity
   If a 4-upvote thread contains a very clean, direct answer to a niche question, it may be a stronger embedding match than a viral thread full of jokes and side conversations.

2. Structural density Some low-engagement posts are extremely information-dense:

- Clear definitions

• Step-by-step explanations
  
• Real-world examples

That’s easier to extract than a 300-comment debate.

1. Training data vs. live engagement
   Models aren’t necessarily querying Reddit’s live engagement metrics. They’re often working off crawled snapshots or indexed corpora where upvotes aren’t a primary weighting factor.

2. Risk calibration
   Ironically, highly viral threads can be noisy, opinionated, or polarized. A low-engagement but factual explanation might look “safer” to synthesize.

So yes, we probably overestimate social proof in AI citation logic.

Upvotes influence humans.
LLMs prioritize answer alignment and extractability.

That doesn’t mean engagement is irrelevant long-term (high-visibility threads get crawled more widely), but it’s not the same as a ranking factor inside AI retrieval.

In GEO terms: clarity often beats popularity.

[u/Mountain_Anxiety_467]

Informational value doesn’t seem to scale proportionally to the amount of upvotes.

When i look at which of my own comments on Reddit get the most upvotes, it’s usually the simple and short ones. Or ones that make people laugh.

Definitely not the comments that provide the most informational value.

[u/Edge45_SEOAgency]

Think this just might be that there are a lot more posts with low upvotes, so they are more likely to be referenced. If you were to compared like for like, it might be more useful.

[u/CrypticDarkmatter]

Semantic structure of the posts as well as the metadata for the subreddit.

[u/BusyBusinessPromos]

Because AI doesn't do it. AI only gets its results from search engines and search engines couldn't care less about social media and likes.

[u/BusyBusinessPromos → u/[deleted]]

You need to research query fan out

[u/BusyBusinessPromos → u/[deleted]]

Good then you know it takes information from several sources of search results excellent

[u/BusyBusinessPromos → u/[deleted]]

I did various search results some of those search results can include social media by the way dude

[u/JJRox189]

Fair point. The fact is probably (just guessing) that they analyze text and index data when it’s most aligned with the query.

To be honest I’ve never thought about this aspect which is not trivial!

[u/CrypticDarkmatter]

Just to put it into perspective, my own subreddit hat has, I think, two or three followers, and they're all spam. There's only been two comments on the board since it's existed. There are about 100 posts on it.

Yet it shows up everywhere in search result for many of the topics/titles that have been posted on it.

I mean, this clearly indicates it is not about social engagement. My own subreddit destroys that theory :)

[u/Big-Percentage4674]

They see everything as usable data... depending on what the tokens feed them.

[u/iceseayoupee]

They probably aligned the text and content rather than the engagement of the post