mlsanityData to 7 Oct 2026

Empowering NGOs in Countering Online Hate Messages

arXiv 2107.02472 ↗First posted 6 Jul 2021cs.CL cs.AI cs.CYcited by 13

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Abstract (arXiv)

Studies on online hate speech have mostly focused on the automated detection of harmful messages. Little attention has been devoted so far to the development of effective strategies to fight hate speech, in particular through the creation of counter-messages. While existing manual scrutiny and intervention strategies are time-consuming and not scalable, advances in natural language processing have the potential to provide a systematic approach to hatred management. In this paper, we introduce a novel ICT platform that NGO operators can use to monitor and analyze social media data, along with a counter-narrative suggestion tool. Our platform aims at increasing the efficiency and effectiveness of operators' activities against islamophobia. We test the platform with more than one hundred NGO operators in three countries through qualitative and quantitative evaluation. Results show that NGOs favor the platform solution with the suggestion tool, and that the time required to produce counter-narratives significantly decreases.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 15 of its 57 references that are in the map. First posted on arXiv 6 Jul 2021.

Builds on

15 of 57 references.

References · 15

  1. 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,068
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  5. 2020SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)cited by 138
  6. 2019A Benchmark Dataset for Learning to Intervene in Online Hate Speechcited by 128
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  8. 2019CONAN -- COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speechcited by 109
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  10. 2018Thou shalt not hate: Countering Online Hate Speechcited by 64
  11. 2020Generating Counter Narratives against Online Hate Speech: Data and Strategiescited by 58
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3 more
  1. 2018Analyzing the hate and counter speech accounts on Twittercited by 21
  2. 2018But Who Protects the Moderators? The Case of Crowdsourced Image Moderationcited by 9
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 4; 2025: 3; 2026: 2.

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  1. 2022Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Counteringcited by 40
  2. 2022Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Studycited by 30
  3. 2024NLP for Counterspeech against Hate: A Survey and How-To Guidecited by 21
  4. 2023Understanding Counterspeech for Online Harm Mitigationcited by 17
  5. 2023CoSyn: Detecting Implicit Hate Speech in Online Conversations Using a Context Synergized Hyperbolic Networkcited by 12
  6. 2024Low-Resource Counterspeech Generation for Indic Languages: The Case of Bengali and Hindicited by 5
  7. 2024CrowdCounter: A benchmark type-specific multi-target counterspeech datasetcited by 5
  8. 2025Beating Harmful Stereotypes Through Facts: RAG-based Counter-speech Generationcited by 2
  9. 2025HatePRISM: Policies, Platforms, and Research Integration. Advancing NLP for Hate Speech Proactive Mitigationcited by 1
  10. 2026Assisted Counterspeech Writing at the Crossroads of Hate Speech and Misinformationcited by 1
  11. 2024Demarked: A Strategy for Enhanced Abusive Speech Moderation through Counterspeech, Detoxification, and Message Managementcited by 0
  12. 2025Can NLP Tackle Hate Speech in the Real World? Stakeholder-Informed Feedback and Survey on Counterspeechcited by 0
1 more
  1. 2026CATCH-ME if you RAG: a dataset of Contextually Annotated multi-Turn Counterspeech against Hate and Misinformation Exchangescited by 0