PEACE 2.0: Grounded Explanations and Counter-Speech for Combating Hate Expressions
This addresses the challenge of responding to hate speech on online platforms, which is an open problem in NLP, though it appears incremental as it builds on prior detection methods.
The paper tackles the problem of generating counter-speech to combat hate expressions online by introducing PEACE 2.0, a tool that uses a Retrieval-Augmented Generation pipeline to ground explanations in evidence and automatically generate evidence-grounded counter-speech, enabling analysis and response for explicit and implicit hateful messages.
The increasing volume of hate speech on online platforms poses significant societal challenges. While the Natural Language Processing community has developed effective methods to automatically detect the presence of hate speech, responses to it, called counter-speech, are still an open challenge. We present PEACE 2.0, a novel tool that, besides analysing and explaining why a message is considered hateful or not, also generates a response to it. More specifically, PEACE 2.0 has three main new functionalities: leveraging a Retrieval-Augmented Generation (RAG) pipeline i) to ground HS explanations into evidence and facts, ii) to automatically generate evidence-grounded counter-speech, and iii) exploring the characteristics of counter-speech replies. By integrating these capabilities, PEACE 2.0 enables in-depth analysis and response generation for both explicit and implicit hateful messages.