
Ask HN: Is trolling on social media a sign that machine learning is overhyped? - glondi
YouTube comments, Facebook and Twitter are all full of trolls. *<p>Facebook also has lots of business profiles (not pages) that aren&#x27;t trying very hard to pass as people, as well as spam pages, forums and the like also using human profiles<p>With the rise of organized government trolling ops, this issue is becoming much more important.<p>You&#x27;d think that these leading lights would have figured out how to flag bad accounts more effectively than they do, and to train ML models to find similar accounts to those that are closed after manual reporting. But none of this seems to be the case.<p>Could it be that they simply lack the ability to do so? And does that tell us anything about the state of AI and Big Data in 2016?<p>*The classic meaning of &quot;troll&quot; not the generecized insult
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niftich
These are separate issues.

From the perspective of a social network operator who is interested in
personalized data to collect an accurate social graph and ultimately sell ads
(or data), spam accounts are arguably more of a threat than trolls, as spam
accounts will never exhibit 'normal human' behavior like providing truthful
data about their lives or presenting a truthful network of influence.

Troll accounts may in fact promote more engagement (in the most clinical
definition of the word), since both trolls and their victims are actual
humans. But being harassed drives people away so it isn't just a user
retention risk, but also a reputational one.

Outside of social networks, a frequent solution to curb harassment is
community moderation like downvotes, which only works if the majority is on
the side of the victim and not the attacker. When no such consensus exists,
all involved parties will be in disagreement with the opposing side, and any
administrative to adjudicate a decision on who's in the right will wrong at
least half of the participants.

ML may be able to filter out blatantly spammy content, but moderating
adversarial content is something us humans haven't quite solved either.

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auganov
Do we know for a fact that they want to solve this problem?

I'm sure they'd love to change user behavior in a way that would produce more
interesting interactions. But I doubt they truly want to go after the random
fluff and outright delete it. They'd be penalized for it in the short term
(less engagement etc).

What really needs to happen is the general public getting fed up with it.

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seanwilson
I'm guessing programmatically identifying trolls is a very hard problem. You
could identify the really obvious ones from a blacklist of words (e.g.
insulting words, swear words) but I imagine many require real world and topic
specific knowledge to identify (e.g. implying silly things are true, insults
that require parsing a sentence or two to understand).

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throw_away_777
Machine learning is a tool that cuts both ways - sites can use it to try and
find trolls, but trolls can also use it to better automate bots.

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glondi
Most of the pages and accounts I refer to are not bots, but businesses with
obvious names and content, or are run by real people who are from lower wage
countries, and not sophisticated at all.

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benologist
It's a sign of trolling being an unsolved problem, not proof a solution
doesn't exist.

