Social media platforms struggle to protect users from harmful content through content
moderation. These platforms have recently leveraged machine learning models to cope with …

We describe the current content moderation strategy employed by Meta to remove policy-
violating content from its platforms. Meta relies on both handcrafted and learned risk models …

In today's digital world, interaction with online platforms is ubiquitous, and thus content
moderation is important for protecting users from content that do not comply with pre …

Current content moderation practices follow the\textit {trial-and-error} approach, meaning
that moderators apply sequences of interventions until they obtain the desired outcome …

The sheer volume of online user-generated content has rendered content moderation
technologies essential in order to protect digital platform audiences from content that may …

Content moderation on social media is governed by policies that are intricate and frequently
updated with evolving world events. However, automated content moderation systems often …

Successful content moderation in online platforms relies on a human-AI collaboration
approach. A typical heuristic estimates the expected harmfulness of a post and uses fixed …

Despite the growing prevalence of ML algorithms, N LP, algorithmically-driven content
recommender systems and other computational mechanisms on social media platforms …

Is Automated Content Moderation Going to Solve Our Misinformation Problems? Page 1
Page 1 INFORMATION MATTERS https://informationmatters.org | editor@informationmatters.org …

Public debate about content moderation has overwhelmingly focused on removal: social
media platforms deleting content and suspending users, or opting not to do so. However …