Homofilia, polarización afectiva y desinformación en Twitter. Caso de estudio sobre la crisis migratoria #Openarms
Resumen
El Mediterráneo es una de las rutas migratorias más mortíferas del mundo y se ha convertido una vez más en centro de la polémica en relación a la actuación del buque humanitario Open Arms. Este buque, tras rescatar migrantes del mar, estuvo en travesía durante diecinueve días, bloqueado institucionalmente y envuelto en disputas diplomáticas en la Unión Europea. Como reacción, la ciudadanía, distintos actores sociales y la propia ONG Open Arms hicieron uso de Twitter para intercambiar información y expresar opiniones y sentimientos en relación con el fenómeno migratorio. En este artículo se analizan pautas de conectividad e interacción de los usuarios de Twitter en torno al hashtag #Openarms. Tras recoger muestras masivas de tuits con técnicas de extracción, se identificaron los actores sociales con mayor liderazgo mediante análisis de redes sociales. Se han detectado comunidades por medio del algoritmo de modularidad, cuyo contenido ha sido interpretado mediante netnografía. Los resultados evidencian cómo los usuarios de Twitter tienden a congregarse con quienes comparten sus mismas creencias, formándose las denominadas cámaras eco. La interacción en base a este suceso despertó estados emocionales colectivos que dieron lugar a burbujas filtro que potenciaron la desinformación y la polarización entre comunidades.
Palabras clave
Crisis migratoria, redes sociales online, homofilia, desinformación, polarización afectivaCitas
Alamán, A. P. (2011). El término “inmigrantes” en los titulares de prensa: entre interculturalidad e hibridación. Confluenze. Rivista Di Studi Iberoamericani, 3(1), pp. 188–207. https://www.researchgate.net/publication/277272789_El_termino_inmigrantes_en_los_titulares_de_prensa_entre_interculturalidad_e_hibridacion
Allport, G. W. (1954). Formation of in-groups. In The Nature Of Prejuice (25th Anniv, pp. 28–47). Addison-Wesley Publishing Company.
Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. B. F., Lee, J., Mann, M., Merhout, F., & Volfovsky, A. (2018). Exposure to opposing views on social media can increase political polarization. Proc Natl Acad Sci U S A. 115(37). https://doi.org/10.1073/pnas.1804840115
Baker, P., Gabrielatos, C., Khosravinik, M., Krzyżanowski, M., & Mcenery, T. (2011). A useful methodological synergy ? Combining critical discourse analysis and corpus linguistics to examine discourses of refugees and asylum seekers in the UK press. Discourse & Society, 19 (3), pp. 273-306. https://doi.org/10.1177/0957926508088962
Bakhshandeh, R., Samadi, M., Azimifar, Z., & Schaeffer, J. (2011). “Degrees of Separation in Social Networks.” Pp. 18–23 In Proceedings: The Fourth International Symposium on Combinatorial Search, edited by Daniel Borrajo, Maxim Likhachev, and Carlos Linares Lopez. Palo Alto, California: AAAI.
Bakshy, E., Rosenn, I., Marlow, C., & Adamic, L. (2012). The role of social networks in information diffusion. In Proceedings of the 21st International conference on World Wide Web (WWW´12). New York: ACM. pp. 519-528. http://dx.doi.org/10.1145/2187836.2187907
Bakshy, E. Messing, S. & Adamic, L. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348 (6239), pp. 1130-1132. http://dx.doi.org/10.1126/science.aaa1160
Bastian, M., Heymann, S., & Jacomy, M., (2009). Gephi: An Open Source Software for Exploring and Manipulating Networks. Third International AAAI Conference on Weblogs and Social Media, pp.361–362.https://doi.org/10.1136/qshc.2004.010033
Bennett, L., & Iyengar, S., (2008). A new era of minimal effects? The changing foundations of political communication. Journal of communication, 58 (4), pp. 707-731. https://doi.org/10.1111/j.1460-2466.2008.00410.x
Berti, C. (2020). CarRight-wing populism and the criminalization of sea-rescue NGOs: the 'Sea-Watch 3' case in Italy, and Matteo Salvini's communication on Facebook, Media Culture & Society https://doi.org/10.1177/0163443720957564
Bobo, L., & Hutchings, V. L., (1996). Perceptions of racial group competition: Extending Blumer´s theory of group position to a multiracial social context. 61, pp. 951–972.
Boutyline, A., & Willer, R., (2017). The Social Structure of Political Echo Chambers : Variation in Ideological Homophily in Online Networks, Political Psychology 38(3), 551-569. https://doi.org/10.1111/pops.12337
Boxell, L., Gentzkow, M., Shapiro, J. M., (2017). Greater Internet use is not associated with faster growth in political polarization among US demographic groups. Proceedings of the National Academy of Sciences, PNAS 114 (40), pp. 10612-10617. https://dx.doi.org/10.1073%2Fpnas.1706588114
Boyd, D. & Ellison, N. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer‐mediated Communication, Journal of Computer-Mediated Communication, 13 (1), pp. 210-230. http://dx.doi.org/10.1111/j.1083-6101.2007.00393.x
Brader, T. (2006). Campaigns for Hearts and Minds. How Emotional Appeals in Political Ads Work. Chicago, The University of Chicago Press, 280 pp.
Brader, T., Valentino, N. A., & Suhay, E. (2008). What Triggers Public Opposition to Immigration? Anxiety, Group Cues, and Immigration Threat. American Journal of Political Science , 52(4), 959–978.
Brandes, U. (2001). A faster algorithm for betweenness centrality. Journal of mathematical sociology, 25 (2), pp. 163-177. http://dx.doi.org/10.1080/0022250X.2001.9990249
Burke, M., & Kraut, R., (2013, February). Using Facebook after losing a job: Differential benefits of strong and weak ties. Proceedings of the 2013 conference on Computer supported cooperative work. ACM, pp. 1419-1430.http://dx.doi.org/10.1145/2441776.2441936
Castillo de Mesa, J., y García, M. D. L. O. (2017). Identificación de influencers de la intervención social en las redes sociales virtuales. AZARBE, Revista Internacional de Trabajo Social y Bienestar, (6), 81-90.
Castillo de Mesa, J., Gómez Jacinto, L., López Peláez, A. y Palma García, M.O. (2019a). Building relationships on social networking sites from a social work approach. Journal of Social Work Practice, 33:2, 201-215, https://doi.org/10.1080/02650533.2019.1608429
Castillo-de Mesa, J. (2019b). “El Trabajo Social en la era digital”. Madrid: Aranzadi. Thomson Reuters.
Castillo de Mesa, J. & Gómez Jacinto, L. (2020). Digital competences and skills as key factors between connectedness and tolerance to diversity on social networking sites: case study of social work graduates on Facebook. Current Sociology. (Aceptado, pendiente de publicación).
Cohen, J. (2001). Defining Identification : A Theoretical Look at the Identification of Audiences With Media Characters, Mass Communication & Society,4(3), 245–264. https://doi.org/10.1207/S15327825MCS0403_01
Derks, D., Fischer, A.H., & Bos, A.E. (2008). The Role of Emotion in Computer-mediated Communication: A Review. Computers in Human Behavior, 24(3), 766-785. http://dx.doi.org/10.1016/j.chb.2007.04.004
Dias, P. (2014). From ‘infoxication’to ‘infosaturation’: a theoretical overview of the cognitive and social effects of digital immersion, Ámbitos, 24, pp. 8-12.
Edunov, S., Diuk, C., Filiz, I.O., Bhagat, S., y Burke, M. (2016). Three and a half degrees of separation. Research at Facebook. Recuperado el 18 de marzo de 2019 de: https//www.research.facebook.com
European Commission. Eurobarometer interactive. "Fakes news and disinformation online”. https://ec.europa.eu/commfrontoffice/publicopinion/index.cfm/survey/getsurveydetail/instruments/flash/surveyky/2183
Fernández, A. Revilla, A. & Andaluz, L. (2020). Analysis of the discursive characterization of migratory stories on Twitter: The Aquarius case. Revista Latina de Comunicación Social, 77: 1-17
Flaxman, S., Goel, S., & M Rao, J., (2016). Filter bubbles, Echo chambers and Online news consumption. Public Opinion Quarterly, 80, 298–320. https://doi.org/10.1093/poq/nfw006
Fortunati, L., Pertierra, R., & Vincent, J. (2012). Migration, Dias -pora and Information Technology in Global Societies. London:Routledge.
Geertz, C., (1993). Descripción densa: hacia una teoría interpretativa de la cultura. En Bohannan, P. y Glaser, M. (Eds.). Antropología: lecturas. (2.ª ed.). Madrid: McGraw-Hill, pp.547-568.
Gillani, N.; Yuan, A.; Saveski, M., Vosoughi, S., Roy, D. (2018). Me, my echo chamber, and I. Introspection on social media polarization. Proceedings of the 2018 World Wide Web. Conference International World Wide Web Conferences Steering Committee, pp. 823-831.
Girvan, M., & Newman, M. (2002). Community structure in social and biological networks. Proceedings of the national academy of sciences, Proc Natl Acad Sci 99, (12), pp. 7821-7826. http://dx.doi.org/10.1073/pnas.122653799
Han, B. (2014a). En el enjambre. Barcelona: Herder Editorial.
Han, B. (2014b). Psicopolítica. Barcelona: Herder Editorial.
Hine, C. (2005). Virtual Methods: Issues in Social Research on the Internet. Oxford: Berg Publishers.
Hjorth, L., (Ed.)., Horst, H., Galloway, A., & Bell, G. (2017). The Routledge Companion to Digital Ethnography. New York: Routledge. https://doi.org/10.4324/9781315673974
International Organization of Migration. (2015). How the world views migration. https://publications.iom.int/system/files/how_the_world_gallup.pdf
Iyengar, S., & Hahn, Kyu. S. (2009). “Red media, blue media: Evidence of ideological selectivity in media use” , Journal of communication, 59, (1), pp. 19-39. https://pcl.stanford.edu/research/2009/iyengar-redmedia-bluemedia.pdf
Iyengar, S., Sood, G., & Lelkes, Y. (2012). Affect , Not Ideology A Social Identity Perspective on Polarization. 76(3), 405–431. https://doi.org/10.1093/poq/nfs038
Jamieson, K. H., & Cappella, J. (2008). Echo chamber: Rush Limbaugh and the conservative media establishment. Oxford: Oxford University Press.
Kozinets, R. V. (2015). Netnography: redefined. CA: Thousands Oaks Sage.
Kramer, A.D., Guillory, J.E., & Hancock J.T. (2014). Experimental Evidence of Massive-scale Emotional Contagion through Social Networks. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 111(24), 8.788-8.790.
Ksiazek, T.B., (2011). A Network Analytic Approach to Understanding Cross-Platform Audience Behavior, 24 (4) Journal of Media Economics, pp. 237–251. https://doi.org/10.1080/08997764.2011.626985
Latapy, M. (2008). “Main-memory triangle computations for very large (sparse (power-law)) graphs”, Theoretical Computer Science, 407, (1–3), pp. 458–473. https://doi.org/10.1016/j.tcs.2008.07.017
Layman, G. C., & Carsey, T. M. (2002). Party Polarization and Party Structuring of policy attitudes: A Comparison of Three NES Panel Studies, Political Behavior, 24(3), pp. 199–237.
Mancini, T., Sibilla, F., Argiropoulos, D., Rossi, M., Everri, M., (2019). The opportunities and risks of mobile phones for refugees' experience: A scoping review. PLOS ONE, 14(12). https;//10.1371/journal.pone.0225684
Maya-Jariego, I. (2016). 7 usos del análisis de redes en la intervención comunitaria. Redes. Revista hispana para el análisis de redes sociales, 27(2), 1-10. https://doi.org/10.5565/rev/redes.628
O'Reilly, T. (2006). Qué es Web 2.0. Patrones del diseño y modelos del negocio para la siguiente generación del software. Boletín de la Sociedad de la Información: Tecnología e Innovación, 3, pp. 177-201. https://www.analfatecnicos.net/archivos/97.QueEsWeb2.0.pdf
Panger, G. (2018). “People Tend to Wind Down, Not Up, When They Browse Social Media” Proceedings of the ACM on Human-Computer Interaction, 2 (133): https://doi.org/10.1145/3274402
Papacharissi, Z. (2014). Toward New Journalism(s). Affective News, Hybridity, and liminal Spaces. Journalism Studies, 27-40.doi: http://dx.doi.org/10.1080/1461670X.2014.890328
Papacharissi, Z., & Oliveira, F. (2012). Affective News and Net -worked Publics: The Rhythms of News Storytelling on #Egypt.Journal of Communication,62(2), 266-282. http://dx.doi. -org/10.1111/j.1460-2466.2012.01630.x
Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. London: Penguin UK.
Sunstein, Cass. R. (2002). “The law of group polarization”, Journal of political philosophy, 10(2). pp. 175-195. https://onlinelibrary.wiley.com/doi/abs/10.1111/1467-9760.00148
Sunstein, Cass. R. (2009). Going to extremes: How like minds unite and divide. Oxford: Oxford University Press.
Sindermann, C., Elhai, J. D., Moshagen, M., & Montag, C. (2020). Age , gender , personality , ideological attitudes and individual differences in a person ’ s news spectrum : how many and who might be prone to “ fi lter bubbles ” and “ echo chambers ” online ? Heliyon 6(1) https://doi.org/https://doi.org/10.1016/j.heliyon.2020.e03214
Sniderman, P., Hagendoorn, L., & Prior, M. (2004). Predisposing Factors and Situational Triggers : Exclusionary Reactions to Immigrant Minorities. American political Science Review, 98 (1): pp.35-49. https://doi.org/10.1017/S000305540400098X
Sniderman, P., Howell, & G., W. (2017). The Politics of Race, en Sears, DO., Sidanius J., Bobo L.,(Edit). Racialized Politics: Values, Ideology, and Prejudice in American Public Opinion. Chicago: Chicago University Press.
Urchs, S. Wendlinger, L. Mitrovic, J. et. al. (2019). MMoveT15: A Twitter Dataset for Extracting and Analysing Migration-Movement Data of the European Migration Crisis 2015. Conferencia: 28th IEEE International Conference on Enabling Technologies - Infrastructure for Collaborative Enterprises (WETICE) Ubicación: Capri, ITALY Fecha: JUN 12-14. https://pennstate.pure.elsevier.com/en/publications/simulating-real-time-twitter-data-from-historical-datasets
Urueña, A., Ferrari, A., Blanco, D., & Valdecasa, E. (2011). Las Redes Sociales en Internet. Observatorio Nacional de las Telecomunicaciones y de la Sociedad de la Información (ONTSI).Sevilla: Junta de Andalucía. https://www.observatoriodelainfancia.es/oia/esp/documentos_ficha.aspx?id=3614
Van Dijk, T. A. (2009). Discurso y poder. Contribuciones a los estudios críticos del discurso. Barcelona: Editorial GEDISA.
Wang, T. (2013). Big data needs thick data. Ethnography Matters, Recuperado en marzo de 2017 de: http://ethnographymatters.net/2013/05/13/big-data-needs-thick-data/
Wilson, R. E., Gosling, S. D., & Graham, L. T. (2012). A review of Facebook research in the social sciences. Perspectives on psychological science, 7 (3), 203-220. https://doi.org/10.1177/1745691612442904
Wojcieszak, M., & Mutz, D. C. (2009). “Online groups and political discourse: Do online discussion spaces facilitate exposure to political disagreement?” Journal of Communication, 59 (1), pp.40–56. https://doi.org/10.1111/j.1460-2466.2008.01403.x.
Yardi, S. & Boyd, D. (2010). “Tweeting from the town square: Measuring geographic local networks”. Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, 2010, pp.194-201.
Young L. E., Sidnam-Mauch, E., Twyman, M., Wang, L., Jingyi
Xu, J., Sargent, M., Valente, T.W., Ferrara, E., Fulk, J., & Monge, P. (2021). Disrupting the COVID-19 Misinfodemic With Network Interventions: Network Solutions for Network Problems. American Journal of Public Health. 111, 514-519, https://doi.org/10.2105/AJPH.2020.306063
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Derechos de autor 2021 Joaquín Castillo de Mesa, Paula Méndez Domínguez, Domingo Carbonero Muñoz, Luis Gómez Jacinto
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