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Re:Ask HN: Can we delete our accounts? by qwertyforce on Sunday November 27, 2022 @02:20PM (#33765767)
The problem is the data is already archived, indexed, and probably in some machine learning dataset
Re:Ask HN: Can we delete our accounts? by bob1029 on Sunday November 27, 2022 @02:37PM (#33765950)
Exactly. The first thing that popped into my head was "archive.org".

The only thing that ever helped me was setting my HN comment delay to a non-zero integer. That 1-5 minutes is usually when I want to delete something the most.

I think we are relearning some basics about the internet. HN cannot protect you from yourself. If you press the "reply" button, assume that under that button is a synchronous blocking call wherein your comment + username + timestamp go to a database owned by a 3rd party with questionable intentions.

Re:Ask HN: Can we delete our accounts? by shagie on Sunday November 27, 2022 @05:57PM (#33767898)
For any wondering about that 'delay' feature - https://news.ycombinator.com/item?id=231024

It is a field in the settings.

Re:Ask HN: Can we delete our accounts? by MerelyMortal on Sunday November 27, 2022 @02:42PM (#33766005)
Just because an attack can already be carried out by one entity, doesn't mean the attack surface shouldn't be reduced for other entities.
Re:Ask HN: Can we delete our accounts? by pifm_guy on Sunday November 27, 2022 @02:56PM (#33766140)
And before long, someone will make a 'deleted comment finder', which highlights only deleted comments.

Could be especially handy for journalists and law enforcers.

Re:Ask HN: Can we delete our accounts? by shagie on Sunday November 27, 2022 @03:12PM (#33766345)
https://console.cloud.google.com/marketplace/details/y-combi...

> This dataset contains all stories and comments from Hacker News from its launch in 2006 to present. Each story contains a story ID, the author that made the post, when it was written, and the number of points the story received.

> This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets.