Hate speech and social acceptance of migrants in Europe: Analysis of tweets with geolocation

 Carlos Arcila-Calderón, Salamanca (Spain)

 Patricia Sánchez-Holgado, Salamanca (Spain)

 Cristina Quintana-Moreno, Salamanca (Spain)

 Javier-J. Amores, Salamanca (Spain)

 David Blanco-Herrero, Salamanca (Spain)

https://doi.org/10.3916/C71-2022-02

Keywords

Inmigration, refugees, attitude, hate speech, big data, Twitter

Abstract

Hate speech against vulnerable groups is acknowledged as a serious problem for integration and respect for the social diversity existing within the territory of the European Union. The growth of this type of discourse has been supported by the expansion of social media, which have been proven to act as a mechanism for the propagation of crimes against targets such as migrants and refugees, one of the main affected groups. That is why we have conducted the first European study of the social acceptance of migrants and refugees by studying the presence of hate speech. The research is based on the perspective of the theories of intergroup contact and mediated intergroup contact. The methodology includes large-scale longitudinal analysis (2015-2020) of online hate speech on Twitter (N=847,978) and its contrast with existing official indicators. The results suggest that personal intergroup contact is positively corretaled with the support of the local population towards migrants and refugees but mediated intergroup contact is not correlated with hate speech on Twitter. We found evidence that those regions where the support for foreigners was higher, there was a lower level of hate speech on Twitter. This is an advance in the study of hate speech by territories and can help in the formulation of action strategies.

References

Abrams, D., & Hogg, M.A. (2017). Twenty years of group processes and intergroup relations research: A review of past progress and future prospects. Group Processes & Intergroup Relations, 20(5), 561-569. https://doi.org/10.1177/1368430217709536

Link DOI | Link Google Scholar

Abrams, J.R., McGaughey, K.J., & Haghighat, H. (2018). Attitudes toward Muslims: a test of the parasocial contact hypothesis and contact theory. Journal of Intercultural Communication Research, 47(4), 276-292. https://doi.org/10.1080/17475759.2018.1443968

Link DOI | Link Google Scholar

Allport, G.W. (1954). The nature of prejudice. Addison-Wesley.

Link Google Scholar

Alto Comisionado de las Naciones Unidas para los Refugiados (Ed.) (1951). Convención sobre el Estatuto de los Refugiados. https://bit.ly/2Zz2Y70

Link Google Scholar

Arcila-Calderón, C., Amores, J.J., & Stanek, M. (2021). Predicting integration of refugees: Using machine learning and synthetic populations to predict social acceptance of asylum seekers in European regions. In S. Korkmaz, & B. Bircan (Eds.), Data science for migration and mobility. Oxford University Press.

Link Google Scholar

Arcila-Calderón, C., Amores, J.J., Sánchez-Holgado, P., & Blanco-Herrero, D. (2022, en preparación). Developing and evaluating an automatic detector of racist and xenophobic hate speech on Twitter in Spanish using shallow and deep learning [Unpublished].

Link Google Scholar

Arcila-Calderón, C., Blanco-Herrero, D., & Valdez-Apolo, M.B. (2020). Rechazo y discurso de odio en Twitter: Análisis de contenido de los tuits sobre migrantes y refugiados en español. Revista Española de Investigaciones Sociológicas, 172, 21-40. https://doi.org/10.5477/cis/reis.172.21

Link DOI | Link Google Scholar

Arcila-Calderón, C., Blanco-Herrero, D., Frías-Vázquez, M., & Seoane-Pérez, F. (2022). Refugees welcome? Online hate speech and sentiments in Twitter in Spain during the reception of the boat Aquarius. Sustainability, 13(5), 2728. https://doi.org/10.3390/su13052728

Link DOI | Link Google Scholar

Bayer, J., & Bárd, P. (2020). Hate speech and hate crime in the EU and the evaluation ofonline content regulation approaches. Policy Department for Citizens’ Rights and Constitutional Affairs. https://doi.org/10.2861/28047

Link DOI | Link Google Scholar

Bollen, J., Mao, H., & Pepe, A. (2011). Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 450-453. https://bit.ly/3DO1hRR

Link Google Scholar

Broad, G.M., Gonzalez, C., & Ball-Rokeach, S.J. (2014). Intergroup relations in South Los Angeles. Combining communication infrastructure and contact hypothesis approaches. International Journal of Intercultural Relations, 38(1), 47-59. https://doi.org/10.1016/j.ijintrel.2013.06.001

Link DOI | Link Google Scholar

Cabo-Isasi, A., & García-Juanatey, A. (2017). Hate speech in social media: A state-of-the-art-review. https://bit.ly/33bfHi3

Link Google Scholar

Canelón, A.R., & Almansa, A. (2018). Migración: Retos y oportunidades desde la perspectiva de los Objetivos de Desarrollo Sostenible (ODS). Retos, 8(16), 109-120. https://doi.org/10.17163/ret.n16.2018.08

Link DOI | Link Google Scholar

Cinelli, M., Morales, G.D.F., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021). The echo chamber effect on social media. Proceedings of the National Academy of Sciences, 118(9), 1-8. https://doi.org/10.1073/PNAS.2023301118

Link DOI | Link Google Scholar

Ekman, M. (2019). Anti-immigration and racist discourse in social media. European Journal of Communication, 34(6), 606-618. https://doi.org/10.1177/0267323119886151

Link DOI | Link Google Scholar

Esipova, N., Ray, J., & Pugliese, A. (2020). World grows less accepting of migrants. Gallup. https://bit.ly/3uDGL3r

Link Google Scholar

ESS-ERIC Consortium (Ed.) (2021). European Social Survey (ESS). https://bit.ly/3ilifiq

Link Google Scholar

Eurobarómetro (Ed.) (2020). Public opinion in the European Union. https://doi.org/10.2775/460239

Link DOI | Link Google Scholar

Eurobarómetro (Ed.) (s.f). Sondeos periódicos de opinión del Parlamento Europeo. https://bit.ly/3up3rnR

Link Google Scholar

European Commission (Ed.) (2016). The Census Hub: Easy and flexible access to European census data. Publications office of the European Union. https://doi.org/10.2785/52653

Link DOI | Link Google Scholar

Felt, M. (2016). Social media and the social sciences: How researchers employ Big Data analytics. Big Data & Society, 3(1). https://doi.org/10.1177/2053951716645828

Link DOI | Link Google Scholar

Gallacher, J.D., Heerdink, M.W., & Hewstone, M. (2021). Online engagement between opposing political protest groups via social media is linked to physical violence of offline encounters. Social Media + Society, 7(1). https://doi.org/10.1177/2056305120984445

Link DOI | Link Google Scholar

Inter-Parliamentary Union (Ed.) (2015). Migration, human rights and governance. The International Labour Organization/ The United Nations. https://bit.ly/3F0KDjz

Link Google Scholar

Joinson, A. (1999). Social desirability, anonymity, and internet-based questionnaires. Behavior Research Methods, Instruments, & Computers, 31(3), 433-438. https://doi.org/10.3758/bf03200723

Link DOI | Link Google Scholar

Larson, R.B. (2019). Controlling social desirability bias. International Journal of Market Research, 61(5), 534-547. https://doi.org/10.1177/1470785318805305

Link DOI | Link Google Scholar

Müller, K., & Schwarz, C. (2020). Fanning the flames of hate: Social media and hate crime. Journal of the European Economic Association, 19(4), 2131-2167. https://doi.org/10.1093/jeea/jvaa045

Link DOI | Link Google Scholar

Organización de las Naciones Unidas (Ed.) (2015). Agenda 2030 - Objetivo 10. Reducción de las desigualdades. ONU. https://bit.ly/3ulmcZi

Link Google Scholar

Organización de las Naciones Unidas (Ed.) (2018). Global compact for safe, orderly and regular migration. ONU. https://bit.ly/3op7VtL

Link Google Scholar

Organización de las Naciones Unidas (Ed.) (2019). International migration policies. Data booklet. Statistical Papers - United Nations. https://doi.org/10.18356/0a2bc93d-en

Link DOI | Link Google Scholar

Pettigrew, T.F. (1998). Intergroup contact theory. Annual Review of Psychology, 49(1), 65-85. https://doi.org/10.1146/annurev.psych.49.1.65

Link DOI | Link Google Scholar

Salvini, M. [@matteosalvinimi] (2020, October 26). Ecco Il bel regalo di Natale di chi ci odia. Autore di questo scempio schifoso un palestinese [Tweet]. Twitter. https://bit.ly/3IHDIxK

Link Google Scholar

Sampieri, R.H., Collado, C.F., Lucio, P.B., Valencia, S.M., & Torres, C.P.M. (2014). Metodología de la investigación. McGraw-Hill Education. https://bit.ly/3ESaIRq

Link Google Scholar

Sayce, D. (2020). The number of tweets per day in 2020. https://bit.ly/3CZbUB2

Link Google Scholar

Siapera, E., Boudourides, M., Lenis, S., & Suiter, J. (2018). Refugees and network publics on Twitter: Networked framing, affect, and capture. Social Media + Society, 4(1), https://doi.org/10.1177/2056305118764437

Link DOI | Link Google Scholar

Vox [@Vox_es] (2021, March 27). Mientras impiden la movilidad a los españoles, más de 700 inmigrantes ilegales han asaltado nuestras fronteras en los últimos días [Tweet]. Twitter. https://bit.ly/3GAmGQe

Link Google Scholar

Vrysis, L., Vryzas, N., Kotsakis, R., Saridou, T., Matsiola, M., Veglis, A., Arcila-Calderón, C., & Dimoulas, C. (2021). A Web interface for analyzing hate speech. Future Internet, 13(3), 80. https://doi.org/10.3390/fi13030080

Link DOI | Link Google Scholar

We are social/Hootsuite (Ed.) (2021). Digital 2021 October Global Statshot Report. Digital 2021 Global Digital Overview. https://bit.ly/32c89el

Link Google Scholar

Zhang, J.S., Tan, C., & Lv, Q. (2019). Intergroup contact in the wild: Characterizing language differences between intergroup and single-group members in NBA-related discussion forums. In A. Lampinen, D. Gergle & D.A. Shamma (Eds.), Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-35. https://doi.org/10.1145/3359295

Link DOI | Link Google Scholar

Fundref

This research falls within the scope of the international research project “Enhanced migration measures from a multidimensional perspective (HumMingBird)” funded by the European Union under the Horizon 2020 Research and Innovation Programme, with reference number 870661 (https://hummingbird-h2020.eu/). It has also been supported by international research project “Preventing Hate Against Refugees and Migrants (PHARM)” funded by the European Union under the Rights, Equality and Citizenship Programme (2014-2020) with reference number 875217and by the tool Stop-Hate, funded by the Fundación General de la Universidad de Salamanca as a competitive proof of concept within the TCUE plan, with reference PC-TCUE18- 20_016. This work has been supported by the Research Group Observatorio de los Contenidos Audiovisuales (www.ocausal.es) of the University of Salamanca. The authors would also like to explicitily thank the members of the projects by their assistance during the research, specially: Andreas Veglis, Charalampos Dimoulas, Lazaros Vrysis, Nikolaos Vryzas, Sergio Splendore and Martín Oller. The authors want to thank as well the support provided by the operative online infrastructure of the Supercomputing System of Castille and Leon (Scayle). Finally, we would like to thank Guillermo Frutos (Frutos Miranda Traductores) for his translation work.

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Technical information

Received: 04-10-2021

Revised: 22-11-2021

Accepted: 03-12-2021

OnlineFirst: 01-02-2022

Publication date: 01-04-2022

Article revision time: 49 days | Average time revision issue 71: 45 days

Article acceptance time: 60 days | Average time of acceptance issue 71: 70 days

Preprint editing time: 134 days | Average editing time preprint issue 71: 144 days

Article editing time: 179 days | Average editing time issue 71: 189 days

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