4 ms·

This is not a solvable problem. There is no algorithmic way to detect speech that needs to be boosted and deboosted on social media because there is no way to a

This is not a solvable problem. There is no algorithmic way to detect speech that needs to be boosted and deboosted on social media because there is no way to actually algorithmically detect what is truthful and what is just manipulative propaganda and marketing.

drooby 4y ago
Quick! Someone write an AI that classifies the likelihood of informal fallacies.
- brookst 4y ago
  100%
achenatx 4y ago
it isnt about truth or fiction, it is negative/hate tweets. I run a politics forum and the one rule is no insulting other people, groups, or positions. This makes for a very civil, but bland conversation. People engage with negative/hate tweets. I personally like talking politics without insults, but most people are incapable of it. It is easy to detect insults.
- tclancy 4y ago
  Ok, now scale to a few hundred millions users in lots of languages.
  - disgruntledphd2 4y ago
    Not even just language, but culture subculture too. This is a very difficult problem.
    - tclancy 4y ago
      You can’t sort sarcasm in all of the New Guinean languages? Amateur.
  - qotgalaxy 4y ago
- lmarcos 4y ago
  I don't know about English, but in other languages you need to know the context to distinguish "hate" speech and insults. If I call someone "You, motherf*er!", without context you don't know if I'm insulting that person or just acknowledging my friend who just made a great joke.
  - Shared404 4y ago
    Ditto for English. Very common for that exact interaction in fact.
- disgruntledphd2 4y ago
  That's a truly amazing viewpoint, I honestly can't imagine how one could express the solution that clearly. In case you can't guess, I'm not serious. However if you download a sentiment analysis model and feed it my first paragraph it'll claim it was positive. Sentiment analysis is a really really really hard problem, especially for short texts.
  - LawTalkingGuy 4y ago
    Everyone is assuming OP is meaning ML and that they're in the just-enough-knowledge-to-be-dangerous phase. The problem that needs solving isn't "catch anything that could, upon deciphering, hurt someone's feelings a bit". It's "catch enough despicable or aggressive comments before they cause problems for others". The later is easily doable because part of the signal is the interactions and you only need to damp bad interactions down until they aren't self-sustaining wars across the feeds of the uninterested, not sanitize every post so that they're all toddler-safe. Once you stop trying to prevent bad thoughts and switch to trying to create a good forum it becomes tractable at any scale.
- pixl97 4y ago
  >It is easy to detect insults. I would fully expect the next thing for you to say is "I can program my own Twitter in a week" Trying to figure out language intent is just the kind of thing an engineer/moderator says is easy and then is in deep water a month later after a phrase that means "you're great" in one language means "you're a donkey's anus" in another. When you're moderating a small group it can be somewhat easy, everyone tends to speak the same language, and quite often it just falls into a groupthink that excludes situations like this. But when the situation scales you don't just have users that actively want to use the service, you have adversarial users that want to abuse your service and make it hell... and those users can be exceptionally clever.
  - Avshalom 4y ago
    >>I would fully expect the next thing for you to say is "I can program my own Twitter in a week" as a perfect example you just called achenatx a moron by implying that they would insult twitter employees by implying twitter is trivial. it's an insult by way of a hypothetically ascribed insult and there's no chance in hell that either of them would trigger sentiment detection because they are so context dependent, even worse it's cultural context not textual context
- zimpenfish 4y ago
  > It is easy to detect insults. There is a large corpus of English[1] text that would belie your assertion[3]. Indeed, you could probably just take Hansard and get thousands of non-detectable[2] insults. [1] Other languages are available. [2] At least without causing mass false positives in other text. [3] e.g. "The founders have a vision and they stick rigidly to it." Insult or no?
karmelapple 4y ago
It is a solvable problem: eliminate your algorithm. Facebook and Twitter both grew very popular without an algorithm. Then they chased the almighty engagement metrics.
deleted 4y ago
[deleted]
btbuildem 4y ago
One way to approach that problem could be to eliminate any attempts to boost / temper anyone's tweets altogether.

drooby 4y ago

Quick! Someone write an AI that classifies the likelihood of informal fallacies.

brookst 4y ago
100%

achenatx 4y ago

it isnt about truth or fiction, it is negative/hate tweets. I run a politics forum and the one rule is no insulting other people, groups, or positions. This makes for a very civil, but bland conversation. People engage with negative/hate tweets. I personally like talking politics without insults, but most people are incapable of it. It is easy to detect insults.

tclancy 4y ago
Ok, now scale to a few hundred millions users in lots of languages.
- disgruntledphd2 4y ago
  Not even just language, but culture subculture too. This is a very difficult problem.
  - tclancy 4y ago
    You can’t sort sarcasm in all of the New Guinean languages? Amateur.
- qotgalaxy 4y ago
lmarcos 4y ago
I don't know about English, but in other languages you need to know the context to distinguish "hate" speech and insults. If I call someone "You, motherf*er!", without context you don't know if I'm insulting that person or just acknowledging my friend who just made a great joke.
- Shared404 4y ago
  Ditto for English. Very common for that exact interaction in fact.
disgruntledphd2 4y ago
That's a truly amazing viewpoint, I honestly can't imagine how one could express the solution that clearly. In case you can't guess, I'm not serious. However if you download a sentiment analysis model and feed it my first paragraph it'll claim it was positive. Sentiment analysis is a really really really hard problem, especially for short texts.
- LawTalkingGuy 4y ago
  Everyone is assuming OP is meaning ML and that they're in the just-enough-knowledge-to-be-dangerous phase. The problem that needs solving isn't "catch anything that could, upon deciphering, hurt someone's feelings a bit". It's "catch enough despicable or aggressive comments before they cause problems for others". The later is easily doable because part of the signal is the interactions and you only need to damp bad interactions down until they aren't self-sustaining wars across the feeds of the uninterested, not sanitize every post so that they're all toddler-safe. Once you stop trying to prevent bad thoughts and switch to trying to create a good forum it becomes tractable at any scale.
pixl97 4y ago
>It is easy to detect insults. I would fully expect the next thing for you to say is "I can program my own Twitter in a week" Trying to figure out language intent is just the kind of thing an engineer/moderator says is easy and then is in deep water a month later after a phrase that means "you're great" in one language means "you're a donkey's anus" in another. When you're moderating a small group it can be somewhat easy, everyone tends to speak the same language, and quite often it just falls into a groupthink that excludes situations like this. But when the situation scales you don't just have users that actively want to use the service, you have adversarial users that want to abuse your service and make it hell... and those users can be exceptionally clever.
- Avshalom 4y ago
  >>I would fully expect the next thing for you to say is "I can program my own Twitter in a week" as a perfect example you just called achenatx a moron by implying that they would insult twitter employees by implying twitter is trivial. it's an insult by way of a hypothetically ascribed insult and there's no chance in hell that either of them would trigger sentiment detection because they are so context dependent, even worse it's cultural context not textual context
zimpenfish 4y ago
> It is easy to detect insults. There is a large corpus of English[1] text that would belie your assertion[3]. Indeed, you could probably just take Hansard and get thousands of non-detectable[2] insults. [1] Other languages are available. [2] At least without causing mass false positives in other text. [3] e.g. "The founders have a vision and they stick rigidly to it." Insult or no?

karmelapple 4y ago

It is a solvable problem: eliminate your algorithm. Facebook and Twitter both grew very popular without an algorithm. Then they chased the almighty engagement metrics.

deleted 4y ago

[deleted]

btbuildem 4y ago

One way to approach that problem could be to eliminate any attempts to boost / temper anyone's tweets altogether.