“This paper investigates the role of context in the annotation and detection of online hate and counter speech, where context is defined as the preceding comment in a conversation thread. We created a context-aware dataset for a 3-way classification task on Reddit comments: hate speech, counter speech, or neutral. Our analyses indicate that context is critical to identify hate and counter speech: human judgments change for most comments depending on whether we show annotators the context. A linguistic analysis draws insights into the language people use to express hate and counter speech. Experimental results show that neural networks obtain significantly better results if context is taken into account.”https://aclanthology.org/2022.naacl-main.433/Share this:FacebookXLike this:Like Loading... Post navigation Addressing religious hate online: from taxonomy creation to automated detection (PeerJ) New Human Rights Campaign Foundation Report: Online Hate & Real World Violence Are Inextricably Linked (Human Rights Campaign)