Homofilia, polarización afectiva y desinformación en Twitter. Caso de estudio sobre la crisis migratoria #Openarms

  1. Castillo de Mesa, Joaquín 1
  2. Méndez Domínguez, Paula 1
  3. Carbonero Muñoz, Domingo 2
  4. Gómez Jacinto, Luis 1
  1. 1 Universidad de Málaga
    info

    Universidad de Málaga

    Málaga, España

    ROR https://ror.org/036b2ww28

  2. 2 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Journal:
Redes: Revista hispana para el análisis de redes sociales

ISSN: 1579-0185

Year of publication: 2021

Issue Title: Las redes de habla hispana

Volume: 32

Issue: 2

Pages: 153-172

Type: Article

DOI: 10.5565/REV/REDES.913 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Redes: Revista hispana para el análisis de redes sociales

Abstract

The Mediterranean is one of the deadliest migratory routes in the world and has once again become the center of controversy in relation to the performance of the Spanish ship Open Arms. This ship, after rescueing migrants from the sea, was on a crossing for nineteen days, institutionally blocked and involved in diplomatic disputes in the European Union. As a reaction, the citizens, different social actors and the NGO OpenArms made use of this social networking site Twitter to exchange information and express their opinions and feelings in relation to the migratory phenomenon. This study analyzes the connectivity and interaction patterns of Twitter users around the #Openarms hashtag. Massive samples of tweets have been collected using extraction techniques. Through the analysis of social networks, the social actors with the greatest leadership were identified. Communities have been detected by means of the modularity algorithm, whose content has been interpreted by netnography. The results show how users of the analyzed online social network tend to congregate around those who share the same beliefs, forming the so-called echo chambers. The interaction based on this event aroused collective emotional states that gave rise to filter bubbles that promoted disinformation and polarization between communities.

Bibliographic References

  • 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