The Conference for Machine Learning Innovation

Pre-Moderation – The Safe Sandbox for your Community

Session
Join the ML Revolution!
Register until April15:
✓Save up to 310 €
✓ 2-in-1 conference special
✓10 % Team Discount
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Join the ML Revolution!
Register until April15:
✓Save up to 310 €
✓ 2-in-1 conference special
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now

About fifty thousand questions, answers and comments are published on gutefrage every day. 10% of published items get deleted because they violate gutefrage quality requirements: An item can be of trolling or offensive nature, it can contain forbidden sensitive content or dangerous and illegal information. There are two ways to capture “bad” items: A user can submit a complaint, or it can be stumbled upon by a moderator and then be deleted manually. This approach has two major drawbacks. First, it is time-consuming and cost-inefficient for moderators to rely on luck to find bad content. Second, it negatively affects user experience and creates “broken windows theory” thus causing higher user churn-rate and increasing amount of low-quality content.

To address these problems, we have developed pre-moderation – a system of ML-based classifiers that automatically detects suspicious content based on user characteristics and past behavior combined with content-based features and semantic checks. Depending on classifier confidence, a suspicious item can be either deleted automatically or locked and sent for manual check. The system is continuously monitored and optimized by adjusting model thresholds and retraining. Pre-moderation has enabled us to cost-effectively organize the workload of moderators and to reduce bad content reporting rate.

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Behind the Tracks