"Short is the Road that Leads from Fear to Hate": Fear Speech in Indian WhatsApp Groups
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Abstract (arXiv)
WhatsApp is the most popular messaging app in the world. Due to its popularity, WhatsApp has become a powerful and cheap tool for political campaigning being widely used during the 2019 Indian general election, where it was used to connect to the voters on a large scale. Along with the campaigning, there have been reports that WhatsApp has also become a breeding ground for harmful speech against various protected groups and religious minorities. Many such messages attempt to instil fear among the population about a specific (minority) community. According to research on inter-group conflict, such `fear speech' messages could have a lasting impact and might lead to real offline violence. In this paper, we perform the first large scale study on fear speech across thousands of public WhatsApp groups discussing politics in India. We curate a new dataset and try to characterize fear speech from this dataset. We observe that users writing fear speech messages use various events and symbols to create the illusion of fear among the reader about a target community. We build models to classify fear speech and observe that current state-of-the-art NLP models do not perform well at this task. Fear speech messages tend to spread faster and could potentially go undetected by classifiers built to detect traditional toxic speech due to their low toxic nature. Finally, using a novel methodology to target users with Facebook ads, we conduct a survey among the users of these WhatsApp groups to understand the types of users who consume and share fear speech. We believe that this work opens up new research questions that are very different from tackling hate speech which the research community has been traditionally involved in.
Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 16 of its 72 references that are in the map. First posted on arXiv 7 Feb 2021.
Builds on
16 of 72 references.
References · 16
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4 more
- 2020Deep Learning Models for Multilingual Hate Speech Detectioncited by 49
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Citing papers per year: 2021: 1; 2022: 2; 2023: 5; 2024: 3; 2025: 0; 2026: 2.
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- 2021ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AIcited by 46
- 2023Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Modelscited by 17
- 2024Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Usecited by 17
- 2023Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensivecited by 16
- 2022Detecting Harmful Online Conversational Content towards LGBTQIA+ Individualscited by 8
- 2023On the rise of fear speech in online social mediacited by 5
- 2022Which one is more toxic? Findings from Jigsaw Rate Severity of Toxic Commentscited by 4
- 2024A Community-Centric Perspective for Characterizing and Detecting Anti-Asian Violence-Provoking Speechcited by 4
- 2024Fear and Loathing on the Frontline: Decoding the Language of Othering by Russia-Ukraine War Bloggerscited by 3
- 2023PACO: Provocation Involving Action, Culture, and Oppressioncited by 0
- 2023DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figurescited by 0
- 2026From Emotion to Expression: Theoretical Foundations and Resources for Fear Speechcited by 0
- 2026Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations16 Jul 2026
- 2026From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech23 Jan 2026
- 2024Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Use24 Oct 2024
- 2024Fear and Loathing on the Frontline: Decoding the Language of Othering by Russia-Ukraine War Bloggers19 Sep 2024
- 2024A Community-Centric Perspective for Characterizing and Detecting Anti-Asian Violence-Provoking Speech21 Jul 2024
- 2023Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Models15 Sep 2023
- 2023DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figures31 Jul 2023
- 2023PACO: Provocation Involving Action, Culture, and Oppression19 Mar 2023
- 2023On the rise of fear speech in online social media18 Mar 2023
- 2023Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive29 Jan 2023
- 2022Which one is more toxic? Findings from Jigsaw Rate Severity of Toxic Comments27 Jun 2022
- 2022Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals15 Jun 2022
- 2021ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AIcited by 46
- 2023Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Modelscited by 17
- 2024Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Usecited by 17
- 2023Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensivecited by 16
- 2022Detecting Harmful Online Conversational Content towards LGBTQIA+ Individualscited by 8
- 2023On the rise of fear speech in online social mediacited by 5
- 2022Which one is more toxic? Findings from Jigsaw Rate Severity of Toxic Commentscited by 4
- 2024A Community-Centric Perspective for Characterizing and Detecting Anti-Asian Violence-Provoking Speechcited by 4
- 2024Fear and Loathing on the Frontline: Decoding the Language of Othering by Russia-Ukraine War Bloggerscited by 3
- 2023PACO: Provocation Involving Action, Culture, and Oppressioncited by 0
- 2023DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figurescited by 0
- 2026From Emotion to Expression: Theoretical Foundations and Resources for Fear Speechcited by 0
12 most cited of 13 All 13 (JSON)
- 2026Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations16 Jul 2026
- 2026From Emotion to Expression: Theoretical Foundations and Resources for Fear Speech23 Jan 2026
- 2024Lived Experience Not Found: LLMs Struggle to Align with Experts on Addressing Adverse Drug Reactions from Psychiatric Medication Use24 Oct 2024
- 2024Fear and Loathing on the Frontline: Decoding the Language of Othering by Russia-Ukraine War Bloggers19 Sep 2024
- 2024A Community-Centric Perspective for Characterizing and Detecting Anti-Asian Violence-Provoking Speech21 Jul 2024
- 2023Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Models15 Sep 2023
- 2023DoDo Learning: DOmain-DemOgraphic Transfer in Language Models for Detecting Abuse Targeted at Public Figures31 Jul 2023
- 2023PACO: Provocation Involving Action, Culture, and Oppression19 Mar 2023
- 2023On the rise of fear speech in online social media18 Mar 2023
- 2023Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive29 Jan 2023
- 2022Which one is more toxic? Findings from Jigsaw Rate Severity of Toxic Comments27 Jun 2022
- 2022Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals15 Jun 2022
12 newest of 13 All 13 (JSON)