# 社区健康统计

**URL:** https://meta.discourse.org/t/community-health-statistics/258043
**Category:** Data & reporting
**Tags:** email
**Created:** [2023年三月14日 01:30 UTC](https://meta.discourse.org/t/community-health-statistics/258043 "2023-03-14T01:30:18Z")
**Posts on this page:** 1
**Showing post:** 2

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### Author: ![omarfilip](https://sea3.discourse-cdn.com/meta/user_avatar/meta.discourse.org/omarfilip/32/208019_2.png) [@omarfilip](https://meta.discourse.org/u/omarfilip)
#### Post date: [2023年三月14日 17:56 UTC](https://meta.discourse.org/t/community-health-statistics/258043/2 "2023-03-14T17:56:56Z")

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这将是对社区统计数据的一项绝佳补充。我偶尔会手动使用此数据浏览器脚本进行检查：

> [@Best Practices on reply-by-email](https://meta.discourse.org/t/best-practices-on-reply-by-email/96107/10?u=omarfilip):
>
> Per user: select username, sum(case when (posts.via\_email='t') then 100 else 0 end)/count(posts.id) as perc\_by\_mail, sum(case when (posts.via\_email='t') then 1 else 0 end) cnt\_by\_mail, sum(case when (posts.via\_email\<\>'t') then 100 else 0 end)/count(posts.id) as perc\_not\_by\_mail, sum(case when (posts.via\_email\<\>'t') then 1 else 0 end) cnt\_not\_by\_mail from posts left join users on users.id = posts.user\_id where posts.created\_at \>= now() - interval '4 weeks' group by username All: …

我们目前通过电子邮件收到 16% 的帖子，这是一个相当大的比例。

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