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> Each person along the way is self-moderating because they won't be scamming or harassing their real acquaintances. LMAO. Bernie Madoff got started by roping

> Each person along the way is self-moderating because they won't be scamming or harassing their real acquaintances. LMAO. Bernie Madoff got started by roping in friends and family. Friends and family are literally the biggest targets in every MLM scheme. Family is frequently implicated in identity theft (they have access to your files). Gen-Z has figured out that they can scam their families and cry gay persecution from them to avoid accountability. The vast majority of rape cases (70-90%) are acquaintance rape. Real acquaintances are the most likely to be victimized in literally every form of crime, including murder. Trusted networks only function when people have decency and don't exploit their insider access. > That's why OG Facebook without groups, pages, global recommendations, etc was actually very civil. I'd argue it's because the networks were smaller, and no other reason. When you have a large family, you can afford to fuck over a few members and live with never being invited to Thanksgiving at their house again.

hot_gril 3y ago
The stats would be different if people trusted strangers. Some people are awful to their acquaintances too, but they'll be that way with or without a social network. Can't really do anything about people abusing hard-earned trust. Large network isn't an issue in of itself. Most people indirectly know tons of people. Overly connected is the issue, cause it incentivizes bad things for popularity. Nobody directly knows like 1M people IRL. Even worse if there are no real-life consequences. Maybe we're saying the same thing.
- jstarfish 3y ago
  > The stats would be different if people trusted strangers That's an interesting angle. Trust is the fine line between friend and stranger though. The stats would be different because "acquaintance" no longer has meaning. > Overly connected is the issue, cause it incentivizes bad things for popularity. Yeah, I thought about it some more and shit really went downhill once FB replaced the timeline with the algorithm. That surfaced the worst behavior for attention. You're right about extended networks.
  - hot_gril 3y ago
    https://ncase.me/crowds/ https://ncase.me/crowds/ is what got me thinking about this originally, supposedly based on prior research. It's a bit long and dramatic, so to summarize... They mathematically modeled complex ideas spreading only if they pass a threshold, % of people you know who hold them. Too many connections creates a noise problem for complex ideas, but allows simple ideas to thrive. Simple ideas aren't always bad, but they tend to be, like rage. Too few is also an issue, so there's a sweet spot. Obviously not proof of anything cause it's only a model, but I agree with the theory. Yes FB did go down the toilet with the algo feed, maybe Twitter too. So this is how I judge social networks now.

hot_gril 3y ago

The stats would be different if people trusted strangers. Some people are awful to their acquaintances too, but they'll be that way with or without a social network. Can't really do anything about people abusing hard-earned trust. Large network isn't an issue in of itself. Most people indirectly know tons of people. Overly connected is the issue, cause it incentivizes bad things for popularity. Nobody directly knows like 1M people IRL. Even worse if there are no real-life consequences. Maybe we're saying the same thing.

jstarfish 3y ago
> The stats would be different if people trusted strangers That's an interesting angle. Trust is the fine line between friend and stranger though. The stats would be different because "acquaintance" no longer has meaning. > Overly connected is the issue, cause it incentivizes bad things for popularity. Yeah, I thought about it some more and shit really went downhill once FB replaced the timeline with the algorithm. That surfaced the worst behavior for attention. You're right about extended networks.
- hot_gril 3y ago
  https://ncase.me/crowds/ https://ncase.me/crowds/ is what got me thinking about this originally, supposedly based on prior research. It's a bit long and dramatic, so to summarize... They mathematically modeled complex ideas spreading only if they pass a threshold, % of people you know who hold them. Too many connections creates a noise problem for complex ideas, but allows simple ideas to thrive. Simple ideas aren't always bad, but they tend to be, like rage. Too few is also an issue, so there's a sweet spot. Obviously not proof of anything cause it's only a model, but I agree with the theory. Yes FB did go down the toilet with the algo feed, maybe Twitter too. So this is how I judge social networks now.