Interaction dynamics between hate and counter users on Twitter
Abstract
Social media platforms usually tackle the proliferation of hate speech by blocking/suspending the message or account. One of the major drawback of such measures is the restriction of free speech. In this paper, we investigate the interaction of hatespeech and the responses that counter it (aka counter-speech). One of the prime contribution of this work is that we developed and released1 a dataset where we annotate pairs of hate and counter users.
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Los mensajes de odio publicados por cuentas verificadas han mostrado tener una mayor probabilidad de alcanzar un público amplio debido a su alta credibilidad percibida.
“los mensajes de odio publicados por estas cuentas han mostrado tener una mayor probabilidad de alcanzar un público amplio debido a su alta credibilidad percibida (Maarouf et al., 2024;Mathew et al., 2020).”
From Redes de odio y contranarrativas en Twitter sobre el ataque a iglesias católicas en Algeciras: Dinámicas de conectividad, influencia y polarización (2026) · cites this paper as Mathew et al., 2020
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Rebollo Diaz, C. (2026) · Redes. Revista hispana para el análisis de redes sociales · doi:10.5565/rev/redes.1130
- Authors
- Mathew, B., Kumar, N., Goyal, P., & Mukherjee, A.
- Affiliations
- Indian Institute of Technology Kharagpur (IN)
- Venue
- Proceedings of the 7th ACM IKDD CoDS and 25th COMAD
- Publisher
- ACM
- Published
- 2020-01-05
- Pages
- 116-124
- OpenAlex
- W3000157158
- Cited by
- 22
- References
- 0
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 5 · 2023: 5 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 1
- FWCI
- 1.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Joint International Conference on Data Science & Management of Data (CODS-COMAD) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Keywords
- hate speech, counterspeech, Twitter, annotated dataset, freedom of expression
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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