互联网与文化en.wikipedia.org
1% 规则：互联网参与的不平等分布
1% rule
2014 — 2020，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
这是维基百科关于“1% 规则”的条目：在互联网社区中，大约只有 1% 的用户创造内容，10% 参与互动（如投票、评论），其余 90% 只是潜水浏览。条目还澄清了这一规则常被误解为适用于整个互联网，实际上更适用于单个社区，且不同社区的分布差异很大。
为什么经久不衰：它揭示了在线社区参与度分布的基本规律，对任何做产品、社区或内容的人都有启发，因此多年后仍被反复讨论。
HN 评论精选
用 HN 真实数据验证，结果与 1% 规则大致吻合，但估算方法本身有较大不确定性。
我曾用 HN 的数据算过，结果和这条规则相当吻合。一种算法是今年发过帖的账号数除以访问过 HN 的 IP 数，得到 0.8%；另一种是通过登录用户占比和登录页面浏览占比推算，得到约 8%。两种方法都有缺陷、假设不明，但有意思的是结果几乎差了一个数量级，虽然想说真实值可能在两者之间，但那不过是另一种认知偏差。
dang查看英文原文
I once ran the numbers for HN and was surprised at how closely they matched this rule. Maybe I'll do it again. Edit: here are some estimates. We don't track enough to know about distinct users, so all we can do is guess. The number of accounts that have posted to HN this year, divided by the number of IP addresses that have accessed HN, is 0.008. How close that is to the '1% rule' depends on which is the bigger factor: users with more than one IP or IPs with more than one user. We don't know. If the former is bigger, then 0.008 is a lower bound. Here's another way. The number of accounts that have posted this year, divided by the number of accounts that have viewed HN while logged in, is 0.36. That doesn't tell us much, but we can estimate the ratio of logged-in users to total users this way: logged-in page views divided by total page views. That ratio is 0.23. We can multiply those two to estimate the ratio of posters to total: posters logged-in --------- * --------- logged-in total = 0.36 * 0.23 = 0.0828 So the two ways of estimating produce 0.8% and 8% respectively. Both ways are bogus in that they assume things we don't know and mix units that aren't the same, but they're the two I came up with and I don't remember how I did it before. It's interesting that they're almost exactly an order of magnitude apart. That makes it tempting to say the number is probably in between, but that's another cognitive bias talking.
把 1% 规则当作发帖前的自省工具：你写的东西远比想象中多人看。
希望大家早点内化这条规则。虽然不精确，但我把它理解为：我发的任何东西平均至少有 99 个人在看，再乘以帖子点赞数或粉丝数。发帖前这样想很有帮助。可惜人们还是很容易陷入无意义的争论、情绪化的骂战和钓鱼贴，事后又后悔。
cycloptic查看英文原文
I hope many of us internalized this early. It's not very accurate, but I try to think of this as meaning that on average, everything I post online is being read by a minimum of 99 people, multiplied by either the upvote count on the thread (for HN) or the number of active followers I have (for Twitter). It has helped me to always think this to myself before posting something. I probably am biased from the culture on these sites but it still seems all to easy for people to still get dragged into fruitless discussions, overly emotional flamewars and trollbait that they will regret later.
1% 规则应按单个社区理解，同一个人在不同社区可能既是潜水者又是核心贡献者。
这条规则常被误解为适用于整个互联网，其实只适用于单个社区——有人统计某社区只有 23% 是纯潜水者，17% 是高强度贡献者。每个人可以同时潜水于多个社区，但贡献内容很耗时，所以一个人往往只在一个社区贡献，在其他社区潜水。
Hokusai查看英文原文
> The 1% rule is often misunderstood to apply to the Internet in general, but it applies more specifically to any given Internet community. ... only 23% of the population (rather than 90 percent) could properly be classified as lurkers, while 17% of the population could be classified as intense contributors of content. This is something important to take into account. I can be a lurker in Hacker News but a top contributor in my towns gardeners forum. Any given person has a maximum time that can dedicate to lurk or contribute. But, one hour of lurking has way more coverage than one hour of contributing. e.g. I can read Reddit, Hacker News, and Wikipedia and still have time left to eat breakfast. But, I want to contribute a new Wikipedia article, probably I will need that complete hour or even more. So, I just contribute to 1 community while lurking in the rest.
换个角度看，1% 规则说明创作内容在网络上有巨大的放大效应。
我一直喜欢反过来解读这条规则：网络有放大效应——每有一份内容被创造出来，就有 10 个人在表达意见、100 个人在阅读它。
cstuder查看英文原文
I've always liked the reversed interpretation: The web has a multiplying function. For everything created, there are 10 people expressing an opinion and 100 people reading it.
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