Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderators

arXiv:2311.07879v2 Announce Type: replace
Abstract: 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 load for moderators. Yet, it remains uncertain whether improvements on those tasks have truly addressed moderators' needs in accomplishing their work. In this paper, we surface gaps between past research efforts that have aimed to provide automation for aspects of content moderation and the needs of volunteer content …

abstract aim arxiv automated content moderation cs.ai cs.cl detection identify improvements measuring moderation moderators tasks toxicity toxicity detection type uncertain volunteer