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ALTCHA®

Chat & Forum Moderation

Chat and forum platforms need to moderate user-generated content at scale — beyond just gating account creation, every message or post is a fresh opportunity for spam, abuse, or scams.

What you're defending against

  • Spam and bot-generated content — repetitive or scripted posts.
  • Phishing and malicious links — messages designed to redirect users elsewhere.
  • Hate speech and threatening language.
  • Policy violations — prohibited topics, promotional scams, and similar.
  1. Score every message with Classifier — send the message text (and optional metadata like the sender's email or IP) to POST /v1/classifier and act on the returned classification/score. This alone catches most spam patterns, injection attempts, and — via the URL rule — links to known-phishing domains (see Phishing Detection).
  2. Use Similarity & Training Data to catch reworded variants of spam you've already seen — feed confirmed spam messages into a training-data group (e.g. chat_spam), and match new messages against it with partial: true for short messages.
  3. Add a Rate Limiter on the message-posting endpoint to slow down flooding, independent of content scoring.
  4. Keep improving the training set — route user-reported messages (or anything a moderator confirms as spam/abuse) back into your Similarity groups, so detection gets better over time instead of staying static.

Integration steps

  1. Capture the message/post server-side before it's published.
  2. Send it to the Classifier API, with groups/examples for Similarity matching in the same request if you have a training set.
  3. Compare the returned score against your own threshold: publish immediately, hold for moderator review, or block outright.
  4. When a moderator confirms something as spam or abuse, add it to your training data so similar messages are caught automatically next time.

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