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Topic Modeling and Characterization of Hate Speech against Immigrants on Twitter around the Emergence of a Far-Right Party in Spain

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  • Carlos Arcila Calderón

    (Department of Sociology and Communication, University of Salamanca, Campus Miguel de Unamuno, Paseo Francisco Tomás y Valiente, s/n, 37007 Salamanca, Spain)

  • Gonzalo de la Vega

    (Department of Sociology and Communication, University of Salamanca, Campus Miguel de Unamuno, Paseo Francisco Tomás y Valiente, s/n, 37007 Salamanca, Spain)

  • David Blanco Herrero

    (Department of Sociology and Communication, University of Salamanca, Campus Miguel de Unamuno, Paseo Francisco Tomás y Valiente, s/n, 37007 Salamanca, Spain)

Abstract

In this paper, we sought to model and characterize hate speech against immigrants on Twitter in Spain around the appearance of the far-right party Vox. More than 240,000 tweets that included the term ‘Vox’ between November 2018 and April 2019 were automatically collected and analyzed. Only 1% of the sample included hate speech expressions. Within this subsample of 1977 messages, we found offenses (56%), incitements to hate (42%), and violent speech (2%). The most frequent terms used were classified into five categories: Spain, Immigration, Government, Islam, and Insults. The most common features were foul language, false or doubtful information, irony, distasteful expressions, humiliation or contempt, physical or psychological threats, and incitement to violence. Using unsupervised topic modeling, we found that the four underlying topics (control of illegal immigration, economic assistance for immigrants, consequences of illegal immigration, and Spain as an arrival point for African immigrants and Islamist terrorism) were similar to those in the discourse of Vox. We conclude that the hate speech against immigrants produced around Vox, and not necessarily by Vox, followed the general patterns of this type of speech detected in previous works, including Islamophobia, offensive language more often than violent language, and the refusal to offer public assistance to these collectives.

Suggested Citation

  • Carlos Arcila Calderón & Gonzalo de la Vega & David Blanco Herrero, 2020. "Topic Modeling and Characterization of Hate Speech against Immigrants on Twitter around the Emergence of a Far-Right Party in Spain," Social Sciences, MDPI, vol. 9(11), pages 1-19, October.
    • Handle: RePEc:gam:jscscx:v:9:y:2020:i:11:p:188-:d:433636
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    References listed on IDEAS

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    1. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    2. Karsten Müller & Carlo Schwarz, 2021. "Fanning the Flames of Hate: Social Media and Hate Crime [Radio and the Rise of The Nazis in Prewar Germany]," Journal of the European Economic Association, European Economic Association, vol. 19(4), pages 2131-2167.
    3. Gualda, Estrella & Rebollo, Carolina, 2016. "The Refugee Crisis On Twitter: A Diversity Of Discourses At A European Crossroads," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 4(3), pages 199-212.
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    Cited by:

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    2. Carlos Arcila-Calderón & David Blanco-Herrero & Maximiliano Frías-Vázquez & Francisco Seoane-Pérez, 2021. "Refugees Welcome? Online Hate Speech and Sentiments in Twitter in Spain during the Reception of the Boat Aquarius," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    3. Vicente Javier Clemente-Suárez & Eduardo Navarro-Jiménez & Libertad Moreno-Luna & María Concepción Saavedra-Serrano & Manuel Jimenez & Juan Antonio Simón & Jose Francisco Tornero-Aguilera, 2021. "The Impact of the COVID-19 Pandemic on Social, Health, and Economy," Sustainability, MDPI, vol. 13(11), pages 1-25, June.
    4. Rowe, Francisco & Mahony, Michael & Graells-Garrido, Eduardo & Rango, Marzia & Sievers, Niklas, 2021. "Using Twitter to Track Immigration Sentiment During Early Stages of the COVID-19 Pandemic," SocArXiv pc3za, Center for Open Science.
    5. Yue Su & Sijia Li & Feng Huang & Jia Xue & Tingshao Zhu, 2023. "Exploring the Influencing Factors of COVID-19 Vaccination Willingness among Young Adults in China," IJERPH, MDPI, vol. 20(5), pages 1-17, February.

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