https://code.kryo.se/iodine/

https://blog.torproject.org/introducing-webtunnel-evading-censorship-by-hiding-in-plain-sight/

Yes, this would essentially be a detecting mechanism for local instances. However, a network trained on all available federated data could still yield favorable results. You may just end up not needing IP Addresses and emails. Just upvotes / downvotes across a set of existing comments would even help.

The important point is figuring out all possible data you can extract and feed it to a “ML” black box. The black box can deal with things by itself.

My bachelor’s thesis was about comment amplifying/deamplifying on reddit using Graph Neural Networks (PyTorch-Geometric).

Essentially: there used to be commenters who would constantly agree / disagree with a particular sentiment, and these would be used to amplify / deamplify opinions, respectively. Using a set of metrics [1], I fed it into a Graph Neural Network (GNN) and it produced reasonably well results back in the day. Since Pytorch-Geomteric has been out, there’s been numerous advancements to GNN research as a whole, and I suspect it would be significantly more developed now.

Since upvotes are known to the instance administrator (for brevity, not getting into the fediverse aspect of this), and since their email addresses are known too, I believe that these two pieces of information can be accounted for in order to detect patterns. This would lead to much better results.

In the beginning, such a solution needs to look for patterns first and these patterns need to be flagged as true (bots) or false (users) by the instance administrator - maybe 200 manual flaggings. Afterwards, the GNN could possibly decide to act based on confidence of previous pattern matching.

This may be an interesting bachelor’s / master’s thesis (or a side project in general) for anyone looking for one. Of course, there’s a lot of nuances I’ve missed. Plus, I haven’t kept up with GNNs in a very long time, so that should be accounted for too.

Edit: perhaps IP addresses could be used too? That’s one way reddit would detect vote manipulation.

[1] account age, comment time, comment time difference with parent comment, sentiment agreement/disgareement with parent commenters, number of child comments after an hour, post karma, comment karma, number of comments, number of subreddits participated in, number of posts, and more I can’t remember.

That’s crazy helpful - thanks!

Perfect, thanks a million! I’ll be getting on them soon!

Could you link the page which shows your exact config at that price? I can’t find anything like that. KVM, AMD, Windows VPS - I looked at all three but none suggest the price you’ve written.

That price sounds like a steal, and I’d love to get it if possible. I currently pay $6/month per VPS with Digital Ocean

https://www.racknerd.com/ryzen-vps

From: https://snee.la/stash/#misc (disclaimer: this is my website)

Relevant YouTube Search: Youtube search results become super irrelevant after 6-8 results. Substitute your search query in the %s part of the url (from: /u/FrezNelson on reddit) to remove them.

https://www.youtube.com/results?search_query=%25s&sp=CAASAhAB

@[email protected]

I’m sending this to the guy in the photo :D

(I use Debian on all my machines BTW)

I do use Signal quite a bit. Some important contacts don’t use it and hence, you see my using of WhatsApp.

Yep! Series 4 hasn’t “released” on YouTube yet. I saw Paul William’s story on instagram that they’re releasing Series 5 on TV, but sadly I don’t have access to that. I’m fine being behind by 1-2 years though.

I’m a huge fan of the original British TM, but TM New Zealand is honestly amazing. The whole thing is available on YouTube (thanks Little Alex Horne + team!!!).

In my and many of my friends’ opinion, TM New Zealand Series 2 is one of the best TM series. TM New Zealand in general is absolutely unhinged.

Series 1 feels a bit off, which is probably because it’s unlike British TM. I got used to it fairly quick though.

TM NZ Series 1

TM NZ Series 2

TM NZ Series 3 (final episode releases on YouTube in 2-3 days)

Thank you for your answer :D! I’ll use the equivalent of your national weather service henceforth.

Just out of curiosity, why do you dislike AccuWeather?

Are you talking about this: I have toyota corola?

I think the difference lies in two things:

• You can share an article from a user of a different instance. In this case, your instance will have to look up the rel=“author” tag and check whether the URL is a fediverse instance. I’m not sure whether this is scalable as compared to a tag that directly indicates that the author is on the fediverse. Imagining a scenario where there are 100, 1000, 10,000, or 100,000 instances on different versions.

• The tag is to promote that the author is on the fediverse. If the rel=“author” tag points to twitter for example, maybe Eugen Rochko + team didn’t want a post on the fediverse to link to twitter.

These are my thoughts and idk if they’re valid. But I think just reusing the rel=“author” isn’t the most elegant solution.

I know that mastodon already uses rel=“me” for link verification (I use it on mu website + my mastodon account), but that’s a different purpose - that’s more for verification. There’s still no way of guaranteeing that the rel=“author” tag points to a fediverse account. You’re putting the onus on the mastodon instance.

It works in a pretty neat way:

We’ve decided to create a new kind of OpenGraph tag—the same kind of tags you have on your website to determine which thumbnail image will appear on the preview for the page when shared on Discord, iMessage, or Mastodon. It looks like this: <meta name=“fediverse:creator” content=“@[email protected]” />.

via: https://blog.joinmastodon.org/2024/07/highlighting-journalism-on-mastodon/

Are you in Europe? This is a thing I’ve seen in Europe, but not in other countries.

That checks out - thanks!

I knew about the “Thour” meme, but still didn’t get why the directory turned compressed. My guess is that by licking the lemon, the directory folds in on itself, thus becoming compressed.