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This repository has been archived by the owner on Jun 8, 2022. It is now read-only.
PySlackers is virtually public and open, which makes it vulnerable to trolls. Let's write some basic content moderation automation using Tensorflow to tackle the low hanging fruit: Messages on public channels that contain URLs or uploaded images.
Basically we need to:
Make Slackbot listen to all messages across public channels.
If a message includes a URL that resolves to mime type image/*, run that URL though a pre-trained NSFW classifier (like this one)
Version 1: If content is NSFW, send a message to the admins and maybe a warning to the channel.
The text was updated successfully, but these errors were encountered:
Some version of this seems really useful, perhaps a simple pre-filter is length of membership. While it's easy to game, a 90-day cutoff is likely enough to dissuade troll-types since the instant gratification is gone.
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PySlackers is virtually public and open, which makes it vulnerable to trolls. Let's write some basic content moderation automation using Tensorflow to tackle the low hanging fruit: Messages on public channels that contain URLs or uploaded images.
Basically we need to:
image/*
, run that URL though a pre-trained NSFW classifier (like this one)The text was updated successfully, but these errors were encountered: