Can NLP Tackle Hate Speech in the Real World?: Stakeholder-Informed Feedback and Survey on Counterspeech

Tanvi Dinkar; Aiqi Jiang; Simona Frenda; Poppy Gerrard-Abbott; Nancie Gunson; Gavin Abercrombie; Ioannis Konstas

doi:10.48550/arXiv.2508.04638

Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeech

Tanvi Dinkar, Aiqi Jiang, Simona Frenda, Poppy Gerrard-Abbott, Nancie Gunson, Gavin Abercrombie, Ioannis Konstas

Research output: Working paper › Preprint

Abstract

Counterspeech, i.e. the practice of responding to online hate speech, has gained traction in NLP as a promising intervention. While early work emphasised collaboration with non-governmental organisation stakeholders, recent research trends have shifted toward automated pipelines that reuse a small set of legacy datasets, often without input from affected communities. This paper presents a systematic review of 74 NLP studies on counterspeech, analysing the extent to which stakeholder participation influences dataset creation, model development, and evaluation. To complement this analysis, we conducted a participatory case study with five NGOs specialising in online Gender-Based Violence (oGBV), identifying stakeholder-informed practices for counterspeech generation. Our findings reveal a growing disconnect between current NLP research and the needs of communities most impacted by toxic online content. We conclude with concrete recommendations for re-centring stakeholder expertise in counterspeech research.

Original language	English
Publisher	arXiv
DOIs	https://doi.org/10.48550/arXiv.2508.04638
Publication status	Published - 6 Aug 2025

Keywords

cs.CL

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.48550/arXiv.2508.04638Licence: CC BY

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Cite this

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abstract = "Counterspeech, i.e. the practice of responding to online hate speech, has gained traction in NLP as a promising intervention. While early work emphasised collaboration with non-governmental organisation stakeholders, recent research trends have shifted toward automated pipelines that reuse a small set of legacy datasets, often without input from affected communities. This paper presents a systematic review of 74 NLP studies on counterspeech, analysing the extent to which stakeholder participation influences dataset creation, model development, and evaluation. To complement this analysis, we conducted a participatory case study with five NGOs specialising in online Gender-Based Violence (oGBV), identifying stakeholder-informed practices for counterspeech generation. Our findings reveal a growing disconnect between current NLP research and the needs of communities most impacted by toxic online content. We conclude with concrete recommendations for re-centring stakeholder expertise in counterspeech research.",

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