The thread discussed the question of why people tend to choose proprietary microblogging platfroms (i.e. Bluesky or Threads) over the free and open source microblogging platform, Mastodon.

The reasons, summarised by @noodlejetski@lemm.ee are:

marketing

not having to pick the instance when registering

people who have experienced Mastodon's hermetic culture discouraging others from joining

algorithms helping discover people and content to follow

marketing

and I'm saying that as a firm Mastodon user and believer.

Now that we know why people move to proprietary microblogging platforms, we can also produce methods to counter this.

How do we get "normies" to adopt the Fediverse?

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[–] BeAware@social.beaware.live 49 points 2 months ago* (last edited 2 months ago) (15 children)

@dch82 first, "normies" have to not get harassed when they come here.

Unfortunately the biggest Fedi software refuses to add automated reporting of offensive posts so if it's not reported, the admins won't even see it.

People coming from corporate social media are used to ignoring the report button because in their experience, it either doesn't work, or gets ignored by admins anyway.

We need automated reporting.

@fediverse

[–] Lost_My_Mind@lemmy.world 17 points 2 months ago (2 children)

We need automated reporting.

I'm fine with auto REPORTING, but the actual moderation needs to be a human. Auto moderation is bad. It gets things wrong. It's how I got banned from both twitter (calm down, this was back in 2018 before it was an elon owned nazi cesspool), and reddit.

On twitter I saw a funny video that was posted, and I replied "Aw man, that killed me".

I was banned for "inciting death threats"

[–] BeAware@social.beaware.live 8 points 2 months ago (1 children)

@Lost_My_Mind yeah, just reporting.

I want to do the actual judgement, but if I don't know the post exists, I can't judge anything and it makes me so mad that possible racist stuff can exist on my instance without my knowledge because I havent "seen" it.

@fediverse

[–] p03locke@lemmy.dbzer0.com 2 points 2 months ago

That's the thing about automation and training models.

First, they implement some sort of auto-reporting bot that requires a human to review them. In the beginning, it only about 50% accurate, but as they give it more and more examples of good and bad results through the human reviews, it moves to 80%, then 90%, then 99%, then 99.99% accuracy.

After a while, the humans on the other end are so numb to the 9999 entries they have to mark as approved that they can barely tell what's a rejection themselves, and the moderation team is asking itself just what this human review is actually doing. If it's 99.99% accurate, why not let the bot decide?

Then, the model moves on from auto-reporting to auto-moderation.

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