The guide to content moderation: Introducing crowds to mitigate the challenges of the human moderator

The increased reliance on user-generated content in the business models of online environments brings with it a challenge of setting up rules for content moderation. Namely, how should the firm create a fair and dynamic set of moderation guidelines that will be relevant and explainable? At present, firms are commonly setting the rules as they go and are in need to continuously assess, examine, and update with the help of content experts. Our work seeks to offer a different approach to generating content moderation rules in an economic, dynamic, and objective fashion. Specifically, we propose the use of crowdsourcing in symbiosis with NLP algorithms to compile and revise content moderation guidelines semi-automatically. We discuss how our proposed approach can be integrated into current moderation processes in practice.