Migration recommendation: WireMin

I have been using it for a week and looked into their FAQ page for technology explanation. Here are some pros & cons:

Pros:

1/ 100% Anonymous:

  • No need for an email/phone number to create an ID.
  • Untraceable IP address.
  • End-to-End Encryption (E2EE) for Direct Messages (DMs), Chat rooms, and Blog posts on the Feed.

2/ 100% Censorship resistance:

  • Accounts never get suspended (at least that’s what they say in the FAQ).
  • Content/Messages can only be deleted by the user itself (chat space too, no one can ban you or remove your message).
  • E2EE, no one can decrypt your message, it’s only viewable by you and the recipients.
  • Decentralized, no one can access your content because data is only kept on your device.

Cons:

  • Not enough users, so the whole network is not stable enough due to its decentralized structure.
  • Notifications are only available for DMs, not for Chat space or - - Updates on the following Feed.
  • App crashes occur.
  • Lacks some small features like polls/GIFs.
  • Not open sourced but it is on the dapp store: https://www.alchemy.com/dapps/wiremin

Anyway, I think it could be a good alternative to Twitter/Facebook, due to their privacy issues and monopolistic behaviors. If you are a privacy-focused member, or if you run a sensitive topic community, I think it could be a good choice too.

The only thing I am concerned about is that they are not open source. As for the overall experience, I know they operate on a decentralized structure and personally, I do believe in the safety level of a decentralized network: 100% anonymous, 0 data leaks.

Here is a PrivacyMatters community, https://i.wiremin.com/invite/?g=k49693987788 mainly about TECH and DIGITAL PRIVACY discussion. If you download WireMin for privacy, this can be your first stop.___

  • tryptaminev 🇵🇸 🇺🇦 🇪🇺@feddit.deEnglish
    1·
    1 year ago

    If you have data of a billion people you can analyze enough correlations so that some of them will stick. The problem is, that it is very different from figuring out causation. So you might find a correlation that people with two arts degrees tend to fail their relationships within 6 months, but the issue is not the arts degree but the higher rate of unresolved childhood traumata that led to art as a form of expression.

    Note that the example is entirely off of my head and based on stereotypes. But this is precisely the issue with that kind of data analysis. It is based off on finding stereotypes and if they are used to influence the people through the content they are shown, the products recommended etc., it is reinforcing those stereotypes and changing people towards it.