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@jpangas jpangas commented Jan 24, 2024

Closes #3377
This PR introduces the spamcomment model which is trained to identify spam comments. Later, it will be used to tag potential spam comments.
The model is a work in progress and still needs some features to be added, refined and experimented.

Train on Taskcluster: spamcomment

@jpangas jpangas requested a review from marco-c February 28, 2024 12:09
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@suhaibmujahid suhaibmujahid left a comment

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Thank you, @jpangas! Please see my comments.

Comment on lines 131 to 154
class UnknownLinkAtBeginning(CommentFeature):
name = "Unknown Link found at Beginning of the Comment"

def __init__(self, domains_to_ignore=set()):
self.known_domains = domains_to_ignore

def __call__(self, comment, **kwargs):
urls = extract_urls_and_domains(comment["text"], self.known_domains)["urls"]

words = comment["text"].split()
return words[0] in urls if words else False


class UnknownLinkAtEnd(CommentFeature):
name = "Unknown Link found at End of the Comment"

def __init__(self, domains_to_ignore=set()):
self.known_domains = domains_to_ignore

def __call__(self, comment, **kwargs):
urls = extract_urls_and_domains(comment["text"], self.known_domains)["urls"]

words = comment["text"].split()
return words[-1] in urls if words else False
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Instead, we could return the index for the start of the first link and the index for the end of the last link.

@jpangas wdyt?

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This sounds good. Let me try it out and I will share the results.

@jpangas jpangas marked this pull request as ready for review March 13, 2024 11:08
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jpangas commented Mar 14, 2024

This is currently blocked by #4097

@marco-c marco-c removed their request for review August 5, 2024 16:33
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Create a model to automatically tag spam comments

3 participants