Content moderation is the process of flagging content based on pre-defined platform rules.
There has been a growing need for AI moderators to safeguard users as well as protect the …

Experimenting with a new dataset of 1.6 M user comments from a news portal and an
existing dataset of 115K Wikipedia talk page comments, we show that an RNN operating on …

Recent concerns over abusive behavior on their platforms have pressured social media
companies to strengthen their content moderation policies. However, user opinions on these …

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

Evaluating the effects of moderation interventions is a task of paramount importance, as it
allows assessing the success of content moderation processes. So far, intervention effects …

Large language models (LLMs) have exploded in popularity due to their ability to perform a
wide array of natural language tasks. Text-based content moderation is one LLM use case …

Extensive efforts in automated approaches for content moderation have been focused on
developing models to identify toxic, offensive, and hateful content--with the aim of lightening …

The internet has become a central medium through which 'networked publics' express their
opinions and engage in debate. Offensive comments and personal attacks can inhibit …

Reddit administrators have generally struggled to prevent or contain such discourse for
several reasons including:(1) the inability for a handful of human administrators to track and …

With the growth of Automatic Content Moderation (ACM) on widely used social media
platforms, transparency into the design of moderation technology and policy is necessary for …