Show HN: A decentralized index of banned users and where to find their content

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Before the Ban: because on a long enough timeline, everyone becomes unpopular with someone

Don’t fear the ban hammer

a decentralized index of banned users and where to find their content

Introducing Before the Ban

Before the Ban is a service available to all users of social media (
facebook
twitter
instagram
linkedIn etc). Before the Ban helps you backup your content and continue to share it with the your followers, even if your account is suspended, terminated, or “shadow banned.” It helps users locate your new accounts or URLs after a ban.

If you’re wondering why Before the Ban is needed, then you probably think it’s inconceivable that your account would ever be limited or revoked. You believe that everything you post is uncontroversial. If so, keep in mind the following:

  1. The things you post right now may seem uncontroversial, but could someday be taken as a sign that you are an undesirable person to have on a social media platform.1 And even if your content is still uncontroversial to the vast majority of future users, it may still become a problem for the platform you use, if the people who disagree with you are particularly intolerant.2
  2. No matter how good the algorithm used to find rogue users, the algorithm itself can go rogue, banning people for no clear reason. Algorithms have a hard time distinguishing jokes, sarcasm and meta-commentary from directly offensive content.3 Human moderators themselves have a hard time knowing what is, and isn’t, appropriate to post.

  3. You might already be banned and not know it. Under a “shadow ban,” everything about the service seems to work fine for you, but other uses may not be able to find your content when they search for it, and may not see replies you’ve added to their posts. Before the Ban lets you search for users and content that has been shadow banned.

How it works (simple version)

At it’s core, Before the Ban lets people make claims about their accounts, and allows others to agree or disagree with those claims. For example, suppose a person named Sam Smith claimed to own the domain samsmith.com, and control the username @samsmith for
facebook
twitter
instagram and
linkedIn

Suppose in the future Sam has been “de-platformed” by one of these companies. If Sam was shadow banned, and they registered in advance with Before the Ban, then all of Sam’s content will continue to be searchable and browseable here and through decentralized storage. If Sam is banned outright, any content they backed up will still be available, and Before the Ban provides a way for Sam’s followers to find any other social media accounts that are still be accessible. If Sam loses access to all of these accounts, Sam can still route people to their domain name or RSS feed. Sam could also sign up for new social media accounts, and use Before the Band to let people know about these alternative usernames.

How it really works (nerdy version)

At its core, Before the Ban implements a decentralized web of trust based on assertions and witnesses related to the connection between social media users, individual persons (or personae), and content URIs. The web of trust is overlaid on existing social media networks, and “backed up” to decentralized storage through IPFS. All assertions and witness are, in effect, sets of vertices and edges in a graph database. Each of these “claims” has a globally unique ID related to the hash of the data, and, if the user has declared a public key, the signature validating their possession of the corresponding private key.

Before the Ban uses a trust algorithm that takes into account the number of witnesses for an assertion and the “quality” of those witnesses. This algorithm resembles the original PageRank system used by Google.4 However, a key strength of Before the Ban is that the trust ranking algorithm can be swapped out or forked at any time, by anyone. This should reduce the incentive to game the trust rankings, as there will be an unknown number of ranking systems in use, each one emphasizing different factors and evolving over time to overcome shortcomings.

Matt Asher headshot
Matt Asher is the founder and lead developer of Before the Ban. He spent several years working on decentralized, secure publishing in the web browser. Matt helped build the encrypted messaging service
I.CX and the open source library
EveryBit.js. He was a participant in the very first Decentral/Blockchain hackathon. For more information, visit
Matt’s linkedIn profile.

How can I use the service?

How can I invest or be a part of this project?

First off, excellent! Use the
signup form below and indicate in the comments section how you’d like to contribute.

Sign up now for early access!

  1. nostrademons put it, “One interesting consequence of the Internet is that we’re becoming very aware that for every label you could ascribe to yourself, there is some group out there who holds a deep, visceral hate for that label, so deep that they wish you would just cease to exist.”

    If you’ve posted, and wish to continue to post, about any about the following topics:

    • Meat eating
    • Abortion
    • Capital punishment
    • Circumcision
    • Zoos
    • Any religion
    • Politics

    you may find yourself subject to a ban, especially if the people who disagree with you have political power within the network or are particularly loud and intolerant. (see the next footnote)

  2. Skin in the Game, Nassim Nicholas Taleb explains how the most intolerant group, even if very small, can often get the majority to accommodate their beliefs, to the detriment of the more tolerant majority.

  3. In order to highlight media bias, conservative commentator Candice Owens replaced the word “white” with “black” in some tweets from recently named New York Times editorial board member Sarah Jeong. Owens was promptly banned from Twitter, even though she was trying to highlight the hatefulness of the original posts, not actually endorsing the message her posts contained. Owens had her account quickly restored, but only because Twitter was flooded with complaints from her large and vocal fan base.

  4. See The PageRank Citation Ranking: Bringing Order to the Web

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