Context Sensitivity Estimation in Toxicity Detection

Alexandros Xenos
Ioannis Pavlopoulos
Ion Androutsopoulos
First Monday(2022)


Context-sensitive posts are rare in toxicity de-tection datasets. This fact leads to modelsthat disregard even the conversational context(e.g., the parent post) when they predict toxic-ity. This work introduces the task of context-sensitivity estimation in toxicity detection andpresents. We present and publicly release thefirst dataset that can be used to build context-sensitivity estimation systems.We furthershow that systems trained on our dataset canbe effectively used to detect posts that dependto the parent post, regarding toxicity detection.