I say "simply" because, as I mentioned, it's an invariant—possibly the most consistent phenomenon we've observed on HN [1]. I admit I didn't add any substantiation for this! it would have been too much of a digression. (Not that that ever stopped me before; perhaps I'll make up for it now.)

The interesting question is, if it's so consistent, how can it go unnoticed for so long (as you've reported) and/or get perceived as one-sided ("HN is so anti-A!") when in fact it is almost always two-sided ("HN users are divided on A")?

I believe there's a clear answer: it's because what you notice depends on how you feel [2]. If you like A, or (more precisely) dislike anti-A, you are far more likely to notice anti-A posts. Not only that, but they will make a stronger impression on you than the median post—even the median pro-A post.

These two factors—frequency of impression and impact of impression—combine to create a strong picture of the site as anti-A—so strong that people often use universals like "always" and "never" and "absolutely" when describing it. In reality, HN is a statistical cloud of datapoints and your pre-existing feelings are what determines which datapoints you notice (i.e. frequency) and how strongly they affect you (i.e. impact). [3]

This is why people with strongly opposing views feel the same about how biased HN is, just in opposite directions! i.e. with the A team convinced there's a strong anti-A bias and the B team equally convinced there's a strong anti-B bias. It's simply (<-- that word again) that their feelings cause them to notice different subsets of the available datapoints. Abstract out the directional bit (pro- or anti-A), and their comments become isomorphic.

Unfortunately for us, HN is more afflicted by this phenomenon than sites which allow sharding, whether by social group (e.g. Twitter's follow lists) or content (e.g. Reddit's subreddits), and thus organize the community into silos [4]. HN is non-siloed, meaning everyone is in the same big community: all the As, all the anti-As, all the Bs, and all the anti-Bs - all roaming the same threads and bumping into each other. You are therefore more likely to run into datapoints you dislike and so more likely to feel that the community is biased against your view, and - what's worse - more biased the more strongly you feel!

For me this is sad, because I believe that in reality HN is a somewhat (<-- let's not exaggerate) more thoughtful and tolerant community than most others of the same or greater size, but precisely because of this dynamic, ends up being perceived as less so. (I wrote a thing about this a few years ago, if anyone is interested: https://news.ycombinator.com/item?id=23308098.)

I believe this is why one so often hears about how toxic, nasty, negative HN is—not that it isn't those things! but the relative level of them gets distorted. Human beings simply can't take very much of what they dislike and disagree with before resorting to generalization and other internal barriers. This is basically an immune response. It often takes only a handful of datapoints (3, or 2, or maybe even just 1) before the impression burns into the retina and becomes a permanent image [5].

(In one recent case, some prominent people were agreeing about how terrible and mean Hacker News is, and to prove the point, one of them cited a vile reply he had received. The reply, though, was not from HN—it was from Twitter. He hastened to add "HN is the same"—somewhat self-refutingly, since if that were true, an actual example would have been easy to find. In reality, such vile comments do appear on HN, but the community quickly flags most of them, and moderators eventually flag the rest. This is a good example of the skew in perception I'm talking about.)

, [editing - bear with me...]

[1] https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

[2] I don't mean "you" personally, of course—everyone does this. It's a double whammy of https://en.wikipedia.org/wiki/Negativity_bias and https://en.wikipedia.org/wiki/Clustering_illusion, sometimes described in this way: https://en.wikipedia.org/wiki/Hostile_media_effect.

[3] Lots of past explanation here if anyone wants it: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que....

[4] https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...

[5] https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...