The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Mapping Twitter hate speech towards social and sexual minorities: a lexicon-based approach to semantic content analysis
Open accessAbstract
Though there are currently no statistics offering a global overview of online hate speech, both social networking platforms and organisations that combat hate speech have recognised that prevention strategies are needed to address this negative online phenomenon. While most cases of online hate speech target individuals on the basis of ethnicity and nationality, incitements to hatred on the basis of religion, class, gender and sexual orientation are increasing. This paper reports the findings of the ‘Italian Hate Map’ project, which used a lexicon-based method of semantic content analysis to extract 2,659,879 Tweets (from 879,428 Twitter profiles) over a period of 7 months; 412,716 of these Tweets contained negative terms directed at one of the six target groups. In the geolocalized Tweets, women were the most insulted group, having received 71,006 hateful Tweets (60.4% of the negative geolocalized tweets), followed by immigrants (12,281 tweets, 10.4%), gay and lesbian persons (12,140 tweets, 10.3%), Muslims (7,465 tweets, 6.4%), Jews (7,465 tweets, 6.4%) and disabled persons (7,230 tweets, 6.1%). The findings provide a real-time snapshot of community behaviours and attitudes against social, ethnic, sexual and gender minority groups that can be used to inform intolerance prevention campaigns on both local and national levels.
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“Diversos estudios han identificado a las comunidades musulmanas como uno de los grupos más vulnerables al discurso de odio en línea, junto con las mujeres, las personas migrantes y los miembros de la comunidad LGBTQ+ (Baumgarten et al., 2019;Lingiardi 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 Lingiardi et al., 2020
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Cites
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Barberá, P. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.004 · Cited by 373
Misinformation, Disinformation, and Online Propaganda
Guess, A. M., & Lyons, B. A. (2020) · Social Media and Democracy · doi:10.1017/9781108890960.003 · Cited by 284
A Literature Review of Textual Hate Speech Detection Methods and Datasets
Alkomah, F., & Ma, X. (2022) · Information · doi:10.3390/info13060273 · Cited by 167
Comparing pre-trained language models for Spanish hate speech detection
Plaza-del-Arco, F. M., Molina-González, M. D., López, L. A. U., & Valdivia, M. T. M. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114120 · Cited by 162
Siegel, A. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.005 · Cited by 123
Metadata
- Authors
- Lingiardi, V., Carone, N., Semeraro, G., Musto, C., D’Amico, M., & Brena, S.
- Affiliations
- Sapienza University of Rome (IT)
- University of Pavia (IT)
- University of Bari Aldo Moro (IT)
- University of Milan (IT)
- VOX Diritti – Osservatorio italiano sui diritti, Milan, Italy
- Corresponding author
- Lingiardi, Vittorio
- Venue
- Behaviour & Information Technology
- Publisher
- Informa UK Limited
- Published
- 2019-04-22
- Volume
- 39
- Issue
- 7
- Pages
- 711-721
- ISSN
- 0144-929X (ISSN-L)
- 1362-3001
- OpenAlex
- W2941193813
- Cited by
- 113
- References
- 30
- Citations by year
- 2026: 6 · 2025: 16 · 2024: 16 · 2023: 27 · 2022: 16 · 2021: 8 · 2020: 22 · 2019: 2
- FWCI
- 5.54
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- Locations
- Behaviour and Information Technology (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Cineca Institutional Research Information System (Tor Vergata University) (submittedVersion)
- CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- online hate speech, Twitter, sexual minorities, minority groups, semantic content analysis, women, immigrants, gay and lesbian people, Muslims, Jews, people with disabilities, intolerance prevention
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