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The main issue is actually data. I've hand labeled much of my training set for my website: https://hnprofile.com/

For a problem such as argument identification (which I think is totally possible), it would likely take a hundred thousand or more labeled pieces of data. Meaning it would likely cost thousands of dollars.

Now... if you have people who flag content provide a reason, you have the labels generated for you ;)

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Good point. Good idea. Might even have people guiding the process with many folks in decent communities doing it over time. I imagine almost all decent ones, regardless of group norms, will be against a specific subset of behavior such as trolling, obvious words denoting hate, and specific patterns of heated, pointless argument. So, even a lowest, common denominator among many forums downvotes and flags might be useful. Then, forum-specific methods take over from there.

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> How long have you been working with AI to get to this point?

I've been working on neural networks since 2014, so five years or so. However, at the time I was building them from scratch in OpenCL and CUDA. Now, it would take significantly less time to get up to speed.

I highly recommend Coursera's machine learning course.

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Show laarc: Sentence Classifications with Neural Networks (github.com)
6 points by lettergram to news show 601 days ago | 5 comments

Auto fill for the tags when I'm creating. I recommend something like the select2 library:

https://select2.org/

Mix / match tags for the view, so something such as:

https://www.laarc.io/l/programming|news|dev

Should give me all the stories tagged with any

https://www.laarc.io/l/programming&news&dev

Should give me all the stories tagged with all

https://www.laarc.io/l/!programming

The bang should remove items with that tag from the search. So I may want all topics besides programming for what ever reason.

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2 points by emily 601 days ago

+1 for | and & and !

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Ok, you can combine tags using boolean operators:

https://www.laarc.io/l/!dev&show|ask

(Your examples work as written, too.)

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