Giraud, E.H. orcid.org/0000-0003-0845-9804, Poole, E., de Quincey, E. et al. (1 more author) (2025) Learning from online hate speech and digital racism: From automated to diffractive methods in social media analysis. The Sociological Review. ISSN 0038-0261
Abstract
There has been a dramatic surge in uses of big data analytics and automated methods to detect and remove hate speech from social media, with these methods deployed both by platforms themselves and within academic research. At the same time, recent social scientific scholarship has accused social media data analytics of decontextualizing complex sociological issues and reducing them to linguistic problems that can be straightforwardly mapped and removed. Intervening in these debates, this article draws on findings from two interdisciplinary projects, spanning five years in total, which generated comparative datasets from Twitter (X). Focusing on three issues that we identified and negotiated in our own analysis – which we characterize as problems of context, classification and reproducibility – we build on existing critiques of automated methods, while also charting methodological pathways forward. Informed by theoretical debates in feminist science studies and STS, we set out a diffractive approach to engaging with large datasets from social media, which centralizes tensions rather than correlations between computational, quantitative and qualitative data.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in The Sociological Review is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | automated hate speech detection; digital methods; digital racism; hate speech; Islamophobia; Twitter/X |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Sociological Studies (Sheffield) |
Funding Information: | Funder Grant number ARTS AND HUMANITIES RESEARCH COUNCIL AH/T004460/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Oct 2024 10:51 |
Last Modified: | 20 Jan 2025 11:43 |
Status: | Published online |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/00380261241305260 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:218192 |