Migrant Caravan Crisis: Some Realities About the Public Discourse on Twitter
DOI:
https://doi.org/10.33679/rmi.v1i1.2172Keywords:
migrant caravan, public discourse on Twitter, migration crisis rhetoric, Mexico, Central America.Abstract
The study aims to explore Twitter content to find out the confrontational structure of online public discourse during the migrant caravan crisis of 2018. To carry out this approach, an exploratory quantitative method was chosen to analyze a representative universe of the messages published on the platform from January 1 to February 15, 2019. The findings indicate —among others— that the public discourse on the caravan is transnational, widely stimulated by the media, and for the most part, expresses neutral sentiment. However, the articulation of the media landscape and the rhetorical structure of the migration crisis seem to exhibit similarities and differences between countries of receiving tradition and transit. For the latter, it is suggested to extend the research to other technological means involved in the construction/deconstruction of the migratory narrative.
References
Abroms, L. C. y Craig Lefebvre, R. (2009). Obama's wired campaign: Lessons for public health communication. Journal of Health Communication, 14(5), 415-423. doi: https://doi.org/10.1080/10810730903033000
Albicker Aguilera, S., Castañeda Gómez del Campo, A., Coria Márquez, E., Félix Vega, C., Guillén López, T., París Pombo, M. D., Pérez Duperou, G. y Velasco Ortíz L. (2018). Migrantes haitianos y centroamericanos en Tijuana, Baja California, 2016-2017.
Políticas gubernamentales y acciones de la sociedad civil [Trad. A. Carrier y E. Printemps]. Tijuana: El Colegio de la Frontera Norte/Comisión Nacional de los Derechos Humanos México. Recuperado de https://bit.ly/2IXfP8y
Alto Comisionado de las Naciones Unidas para los Refugiados (ACNUR). (2017). México Factsheet, México: Autor. Recuperado de https://bit.ly/2X7FcIE
Arriola Vega, L. A. (2016). Mexico’s Not-So-Comprehensive Southern Border Plan. Houston: Rice University’s Baker Institute for Public Policy. Recuperado de https://bit.ly/2LpSsGf
Asociación de Internet MX (AIMX). (2019). 15° Estudio sobre los Hábitos de los Usuarios de Internet en México 2018. Movilidad en el Usuario de Internet Mexicano. Recuperado de https://www.asociaciondeinternet.mx/estudios/habitos-de-internet
Avello-Gayo, D., Metaxas, P. y Mustafaraj, E. (21 de julio 2011). Limits of electoral predictions using Twitter [conferencia]. En Proceedings of the International Conference on Weblogs and Social Media. Barcelona: the AAAI Press. Recuperado de https://bit.ly/2Zuu6iM
Bobes León, V. C. y Pardo Montaño, A. M. (2016). Política migratoria en México: Legislación, imaginarios y actores. México: Facultad Latinoamericana de Ciencias Sociales.
Boomgaarden, H. G. y Vliegenthart, R. (2007). Explaining the rise of anti-immigrant parties: The role of news media content. Electoral Studies, 26(2), 404–417. doi: https://doi.org/10.1016/j.electstud.2006.10.018
Boomgaarden, H. G. y Vliegenthart, R. (2009). How news content influences anti- immigration attitudes: Germany, 1993-2005. European Journal of Political Research, 48 (4), 516–542. doi: https://doi.org/10.1111/j.1475-6765.2009.01831.x
Bouvier, G. (2019). How Journalists Source Trending Social Media Feeds. Journalism Studies, 20(2), 212–231. https://doi.org/10.1080/1461670X.2017.1365618
Brooke, J., Tofiloski, M. y Taboada, M. (2009). Cross-Linguistic Sentiment Analysis: From English to Spanish. En G. Angelova, K. Bontecheva, R. Mitkov, N. Nicolov y N. Nikolov (Eds.), Proceedings of International Conference on Recent Advances Natural Language Processing (RANLP) (pp. 50-54). Bulgaria: INCOMA Ltd.
Bruns, A. y Stieglitz, S. (2014). Twitter data: What do they represent? IT–Information Technology, 56(5), 240-245. https://doi.org/10.1515/itit-2014-1049
Castells, M. (2009). Communication Power. New York: Oxford University Press.
Cheng, J., Adamic, L., Alex Dow, P., Kleinberg, J. M. y Leskovec, J. (7 de abril de 2014). Can cascades be predicted? [conferencia]. En Proceedings of the 23rd international conference on World Wide Web. Nueva York. Recuperado de https://bit.ly/2YmVse7
Conover, M., Ratkiewicz, J., Francisco, M., Gonçalves, B., Menczer, F. y Flammini, A. (2011). Political polarization on Twitter [conferencia]. En Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media. Barcelona: AAAI Press. Recuperado de https://bit.ly/2XezI2C
Durand, J. (2016). Historia mínima de la migración México-Estados Unidos. Ciudad de México: El Colegio de México.
El Colegio de la Frontera Norte (El Colef). (2018). La caravana de migrantes centroamericanos en Tijuana 2018 (Primera etapa). Diagnóstico y propuestas de acción. Tijuana: Autor. Recuperado de https://bit.ly/2MCxy95
EL Colef. (2019a). La caravana de migrantes centroamericanos en Tijuana 2018-2019 (segunda etapa) . Tijuana: Autor. Recuperado de https://bit.ly/2XzI3L7
EL Colef. (2019b). La caravana centroamericana de migrantes en Piedras Negras, Coahuila 2019. Diagnóstico y Propuestas de acción. Tijuana: Autor. Recuperado de https://bit.ly/2FW0IcO
El Qadim, N. (2010). La politique migratoire européenne vue du Maroc : contraintes et opportunités. Politique européenne, 2(31), 91-118. doi : http://doi.org/10.3917/poeu.031.0091
Ernst, N., Engesser, S., Büchel, F., Blassnig, S. y Esser, F. (2017). Extreme parties and populism: an analysis of Facebook and Twitter across six countries. Information, Communication & Society, 20(9), 1347-1364. doi: https://doi.org/10.1080/1369118X.2017.1329333
Ferra, I. y Nguyen. D. (2017). "#Migrantcrisis: “tagging” the European migration crisis on Twitter". Journal of Communication Management, 21(4), 411–426.
Ferrara, E. y Yang, Z. (2015). Quantifying the effect of sentiment on information diffusion in social media. PeerJ Computer Science, 1(e26), 1-15. doi: https://doi.org/10.7717/peerj-cs.26
Gerlitz, C. y Rieder, B. (2013). Mining one percent of Twitter: Collections, Baselines, Sampling. M/C Journal, 16 (2). Recuperado de https://bit.ly/1ogyyqP
Igartua, J. J. y Cheng, L. (2009). Moderating effect of group cue while processing news on immigration. Is framing effect a heuristic process? Journal of Communication, 59(4), 726-749. doi: https://doi.org/10.1111/j.1460-2466.2009.01454.x
Iyengar, S. y Simon, A. F. (2000). New perspectives and evidence on political communication and campaign effects. Annual review of psychology, 51, 149-169. doi: https://doi.org/10.1146/annurev.psych.51.1.149
Karatzogianni, A., Nguyen, D. y Serafinelli, E. (2016). The Digital Transformation of the Public Sphere Conflict, Migration, Crisis and Culture in Digital Networks. Londres: Palgrave Macmillan.
Khiabany, G. (2016). Refugee crisis, imperialism and pitiless wars on the poor. Media, Culture & Society, 38(5), 755–762. doi: https://doi.org/10.1177%2F0163443716655093
Kingsley, P. (28 de Agosto de 2015). Migrant crisis: up to 200 dead after boat carrying refugees sinks off Libya, The Guardian. Recuperado de https://bit.ly/2k4PX0Q>https://bit.ly/2k4PX0Q
Koylu, C., Larson, R., Dietrich. B. J. y Lee, K. (2018). CarSenToGram: geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter. Cartography and Geographic Information Science, 46(1), 57–71. doi: https://doi.org/10.1080/15230406.2018.1510343
Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, 5(1), 1–167. doi: https://doi.org/10.2200/S00416ED1V01Y201204HLT016
Lomborg, S. y Bechmann, A. (2014). Using APIs for data collection on social media. The Information Society, 30 (4), 256-265. doi: https://doi.org/10.1080/01972243.2014.915276
Martínez Hernández-Mejía, I. (2018). Reflexiones sobre la caravana migrante. Análisis Plural, 231-248. Recuperado de http://hdl.handle.net/11117/5616
Meraz, S. y Papacharissi, Z. (2013). Networked Gatekeeping and Networked Framing on #Egypt. The International Journal of Press/Politics, 18(2), 138-166. doi: https://doi.org/10.1177%2F1940161212474472
Morstatter, F., Pfeffer, J., Liu, H. y Carley, K.M. (21 de junio de 2013). Is the Sample Good Enough? Comparing Data from Twitter’s Streaming API with Twitter’s Firehose [conferencia]. En The Proceedings of the Seventh International AAAI Conference on Weblogs and Social Media. Massachusetts: The AAAI Press. Recuperado de http://arxiv.org/abs/1306.5204
Nail, T. (2016). A Tale of Two Crises: Migration and Terrorism after the Paris Attacks. Studies in Ethnicity and Nationalism, 16(1), 158-167.
Nguyen, D. (2016). Anaysing Transnational Web Spheres. The European Example during the Eurozone Crisis. En A. Karatzogianni, D. Nguyen y E. Serafinelli (Eds.), The Digital Transformation of the Public Sphere. Conflict, Migration, Crisis and Culture in Digital Networks (pp. 211-234). Londres: Palgrave Macmillan.
Paulussen, S. y Harder, R.A. (2014). Social Media References in Newspapers: Facebook, Twitter and YouTube as Sources in Newspaper Journalism. Journalism Practice, 8(5), 542–551. https://doi.org/10.1080/17512786.2014.894327
Secretaria de Gobernación (Segob). (2019). Estadísticas de la Coordinación General de la Comisión Mexicana de Ayuda a Refugiados. México: Autor. Recuperado de https://bit.ly/2Gjq6tK
Sloan, L. y Morgan, J. (2015). Who Tweets with Their Location? Understanding the Relationship between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter. PLoS ONE, 10(11), 1-15. doi: http://doi.org/10.1371/journal.pone.0142209
Stephens, M. y Poorthuis, A. (2015). Follow thy neighbor: Connecting the social and the spatial networks on Twitter. Computers, Environment and Urban Systems, 53, 87–95. doi: https://doi.org/10.1016/j.compenvurbsys.2014.07.002
Takhteyev, Y., Gruzd, A. y Wellman, B. (2012). Geography of Twitter Networks. Social Networks, 34(1), 73–81. http://doi.org/10.1016/j.socnet.2011.05.006
Tandoc, E. y Johnson, E. (2016). Most students get breaking news first from Twitter. Newspaper Research Journal, 37(2), 153-166.
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D. y Kappas, A. (2010). Sentiment strength detection in short informal text. Journal of the American Society for Information Science and Technology, 61(12), 2544-2558. doi: https://doi.org/10.1002/asi.21416
Tumasjan, A., Sprenger, T. O., Sandner, P. G. y Welpe, I. M. (2010). Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment [conferencia]. En Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media. Washinton: The AAAI Press. Recuperado de https://bit.ly/1ZYYfRd
Vidal, V. y Musset, A. (2015). Les territoires de l’attente. Francia : Presses universitaires de Rennes.
Vilares Calvo, D., Thelwall, M. y Alonso, M.A. (2015). The megaphone of the people? Spanish SentiStrength for real-time analysis of political tweets. Journal of Information Science, 41(6), 799-813. doi: https://doi.org/10.1177%2F0165551515598926
Vilares, D., Alonso, M. Á. y Gómez-Rodríguez, C. (2015). A syntactic approach for opinion mining on Spanish reviews. Natural Language Engineering, 21 (1), 139-163.
Vliegenthart, R., Schuck, A. R. T., Boomgaarden, H. G. y de Vreese, C. H. (2008). News Coverage and Support for European Integration, 1990-2006. International Journal of Public Opinion Research, 20(4), 415–439. doi: https://doi.org/10.1093/ijpor/edn044
Yaqub, U., Chun, S. A., Atluri, V. y Vaidya, J. (2017). Analysis of political discourse on Twitter in the context of the 2016 US presidential elections. Government Information Quarterly, 34(4), 613-626. doi: https://doi.org/10.1016/j.giq.2017.11.001
Yrizar Barbosa, G. y Alarcón, R. (2010). Emigration Policy and State Governments in Mexico. Migraciones internacionales, 5(19), 165-198. https://doi.org/10.17428/rmi.v5i19.1074
Zimmer, M. y Proferes, N. J. (2014). A topology of Twitter research: Disciplines, methods, and ethics. Aslib Journal of Information Management, 66(3), 250– 261.
Zimmerman, C., Stein, M.-K., Hardt, D. y Vatrapu, R. (2015). Emergence of things felt: harnessing the semantic space of Facebook feeling tags [conferencia]. En Thirty Sixth International Conference on Information Systems, Fort Worth 2015. Texas, E.E. U.U: Association for Information Systems.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Migraciones Internacionales

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors publishing work in this journal agree to the following conditions:
Authors retain copyright and assign first publication rights to the journal Migraciones Internacionales (MI), with the texts registered under an Attribution-NonCommercial-NoDerivatives 4.0 International Creative Commons license (CC BY-NC-ND 4.0), which allows third parties to use published material provided they give credit to the authors and acknowledge this journal as the first publisher.
They authorize the reproduction, publication, translation, communication, and transmission of their paper and all accompanying material, publicly and in any form and by any means; its public distribution in as many copies as required; and public communication thereof in any form, including making it available to the public through electronic means or any other technology, and solely for dissemination and scientific, cultural, and non-commercial purposes.
Authors may enter into further independent contractual agreements for the non-exclusive distribution of the version of the paper published in this journal (for instance, to include it in an institutional repository or personal webpage, or publish it in a book), provided it is not for commercial purposes and they clearly state that the work was first published in Migraciones Internacionales (MI) [and add the corresponding bibliographical record: Author/s (Year). Title of paper. Migraciones Internacionales, volume (number), pp. doi: xxxx].
To that end, authors must submit the form assigning ownership of first publication rights, duly completed and signed. This document is to be uploaded in PDF format as a complementary file on the OJS platform.
This work is released under an Attribution-NonCommercial-NoDerivatives 4.0 International Creative Commons license (CC BY-NC-ND 4.0)..