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The fundamental problem in toxicity detection task lies in the fact that thetoxicity is ill-defined. This causes us to rely on subjective and vague data inmodels' training, which results in non-robust and non-accurate results: garbagein - garbage out.  This work suggests a new, stress-level-based definition of toxicity designedto be objective and context-aware. On par with it, we also describe possibleways of applying this new definition to dataset creation and model training.

On the definition of toxicity in NLP