The Conference for Machine Learning Innovation

Pre-Moderation – The Safe Sandbox for your Community

Session
Join the ML Revolution!
Until June 2
✓ Save up to 226€
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until June 2
✓ Save up to 226€
✓ Group discount
✓ Special discount for freelancers
Register Now
Thank you for attending!
Register Now
Thank you for attending!
Register Now
Join the ML Revolution!
Register until conference starts:
✓ 2 in 1 conference special
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until conference starts:
✓ 2 in 1 conference special
✓ 10 % Team Discount
Register Now
Infos
Wednesday, December 8 2021
14:30 - 15:15
Room:
Salon 2

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.

This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Munich Munich .

This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Singapore Singapore .

Take me to the full program of Zum vollständigen Programm von Berlin Berlin .

This Session Diese Session belongs to the gehört zum Programm von BerlinBerlin program. Take me to the current program of . Hier geht es zum aktuellen Programm von Munich Munich , Singapore Singapore or oder Berlin Berlin .

Behind the Tracks