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Revista Comunicar 71: Discursos de odio en comunicación: Investigaciones y propuestas (Vol. 30 - 2022)

Discurso de odio y aceptación social hacia migrantes en Europa: Análisis de tuits con geolocalización

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

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

Carlos Arcila-Calderón

Patricia Sánchez-Holgado

Cristina Quintana-Moreno

Javier-J. Amores

David Blanco-Herrero

Abstract

El discurso de odio contra públicos vulnerables es reconocido como un grave problema para la integración y el respeto a la diversidad social dentro de la Unión Europea. El aumento de este tipo de discurso se ha visto reforzado con la expansión de las redes sociales, donde se ha demostrado que actúan como mecanismo de propagación de delitos contra colectivos como los migrantes y refugiados, uno de los principales afectados. Por ello se aborda el desarrollo del primer estudio europeo de la aceptación social de migrantes y refugiados mediante el estudio de la presencia de discurso de odio. La investigación se basa en la perspectiva de la teoría del contacto intergrupal y el contacto intergrupal mediado. La metodología incluye el análisis longitudinal (2015-2020) a gran escala del discurso de odio en línea en Twitter (N=847.978) y el contraste con indicadores oficiales existentes. Los resultados apuntan a que el contacto intergrupal personal está correlacionado positivamente con el apoyo de la población hacia migrantes y refugiados, pero el contacto intergrupal mediado no está correlacionado con la disminución del discurso de odio. Encontramos evidencia que muestra que en aquellas regiones en las que el apoyo al colectivo era mayor existía un menor nivel de discurso de odio en Twitter. Esto supone un avance en el estudio del discurso de odio por territorios y puede ayudar en el planteamiento de estrategias de actuación.

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.

Keywords

Inmigración, refugiados, actitud, discurso del odio, big data, Twitter

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

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Referencias

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

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

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

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

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.

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].

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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