Content moderation at scale - Protecting integrity of online communities on Meta platforms

Type of session: talk Track: 1 (HENDERSON THEATRE)
Start Time: 14.00

To enable content moderation on large social media platforms it is important to timely detect harmful viral content. The detection problem is difficult because content virality results from interactions between user interests, content characteristics, feed ranking, and community structure.

This talk will shed the light on the design of the algorithms which can efficiently solve this problem at Meta scale.

Session takeaways

  • Insights into integrity problems on social media platforms


I am a research scientist on the Facebook Research team, working on understanding and modelling large-scale user behaviour.

Before joining Facebook I worked as a data scientist at Skyscanner and as a researcher at King’s College London. My research interests lie on the intersection between systems design, data analysis and machine learning.

Note: Speaker information is subject to change

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