A Semi-supervised Content Moderation Tool for Abusive Language Detection using Transformer Models and Few-Shot Learning

This thesis will show how a technical artifact could be de- veloped as part of a master’s thesis in the study of information systems that could leverage state-of-the-art advances in machine learning, namely transformer models, to bundle their capability into a web application that facilitates moderators to detect problematic content.