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Demarked: A Strategy for Enhanced Abusive Speech Moderation through Counterspeech, Detoxification, and Message Management

arXiv 2406.19543 ↗First posted 27 Jun 2024cs.CL cs.SIcited by 0

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Abstract (arXiv)

Despite regulations imposed by nations and social media platforms, such as recent EU regulations targeting digital violence, abusive content persists as a significant challenge. Existing approaches primarily rely on binary solutions, such as outright blocking or banning, yet fail to address the complex nature of abusive speech. In this work, we propose a more comprehensive approach called Demarcation scoring abusive speech based on four aspect -- (i) severity scale; (ii) presence of a target; (iii) context scale; (iv) legal scale -- and suggesting more options of actions like detoxification, counter speech generation, blocking, or, as a final measure, human intervention. Through a thorough analysis of abusive speech regulations across diverse jurisdictions, platforms, and research papers we highlight the gap in preventing measures and advocate for tailored proactive steps to combat its multifaceted manifestations. Our work aims to inform future strategies for effectively addressing abusive speech online.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 26 of its 75 references that are in the map. First posted on arXiv 27 Jun 2024.

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26 of 75 references.

References · 26

  1. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 736
  2. 2020HateXplain: A Benchmark Dataset for Explainable Hate Speech Detectioncited by 407
  3. 2018Large Scale Crowdsourcing and Characterization of Twitter Abusive Behaviorcited by 270
  4. 2019Multilingual and Multi-Aspect Hate Speech Analysiscited by 133
  5. 2018Fighting Offensive Language on Social Media with Unsupervised Text Style Transfercited by 55
  6. 2019Offensive Language and Hate Speech Detection for Danishcited by 49
  7. 2021Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLPcited by 47
  8. 2021SWSR: A Chinese Dataset and Lexicon for Online Sexism Detectioncited by 42
  9. 2020Hate Speech detection in the Bengali language: A dataset and its baseline evaluationcited by 37
  10. 2021Detecting Harmful Content On Online Platforms: What Platforms Need Vs. Where Research Efforts Gocited by 33
  11. 2022Hate Speech and Counter Speech Detection: Conversational Context Does Mattercited by 32
  12. 2022Inducing Positive Perspectives with Text Reframingcited by 31
14 more
  1. 2020Artificial Intelligence for Social Good: A Surveycited by 29
  2. 2020DeepHateExplainer: Explainable Hate Speech Detection in Under-resourced Bengali Languagecited by 26
  3. 2022Hate Speech and Offensive Language Detection in Bengalicited by 19
  4. 2021How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impactcited by 18
  5. 2020Towards A Friendly Online Community: An Unsupervised Style Transfer Framework for Profanity Redactioncited by 17
  6. 2024Counterspeakers' Perspectives: Unveiling Barriers and AI Needs in the Fight against Online Hatecited by 15
  7. 2021Methods for Detoxification of Texts for the Russian Languagecited by 13
  8. 2021Empowering NGOs in Countering Online Hate Messagescited by 13
  9. 2023Counterspeeches up my sleeve! Intent Distribution Learning and Persistent Fusion for Intent-Conditioned Counterspeech Generationcited by 13
  10. 2020Reducing Unintended Identity Bias in Russian Hate Speech Detectioncited by 10
  11. 2023The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Mediacited by 10
  12. 2022Counter Hate Speech in Social Media: A Surveycited by 5
  13. 2022CoRAL: a Context-aware Croatian Abusive Language Datasetcited by 4
  14. 2024Exploring Boundaries and Intensities in Offensive and Hate Speech: Unveiling the Complex Spectrum of Social Media Discoursecited by 4

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