Aprendizaje automático para el análisis cross-plataforma de la comunicación política: Gobierno y oposición argentinos en Facebook, Instagram y Twitter
DOI:
https://doi.org/10.7764/cdi.55.52631Palabras clave:
redes sociales, Twitter, Instagram, Facebook, Argentina, política, procesamiento del lenguaje natural, modelado de tópicosResumen
Este artículo indaga acerca de la comunicación política en las distintas plataformas, aplicando métodos de las ciencias de datos para analizar similitudes y diferencias entre las publicaciones en Facebook, Instagram y Twitter de 50 políticos argentinos durante 2020. Es un estudio pionero en la región entre los trabajos cross-plataformas y sus objetivos son heurísticos y metodológicos. En relación a lo primero, se demuestra que hay estrategias diferentes según las plataformas: Twitter es el terreno de controversias e interpelaciones entre los políticos y allí la toxicidad es recompensada, mientras que en Facebook e Instagram los políticos despliegan los tópicos en los que parecen considerarse más fuertes. Así, el estudio cross-plataformas permite observar que aun en un contexto polarizado como el argentino existen temas comunes y sin polémicas entre sectores opuestos. En lo metodológico, utilizamos métodos novedosos e implementamos un reciente algoritmo de detección de tópicos, aplicamos análisis de sentimiento con el objetivo de entender si son textos positivos o negativos, y redes neuronales profundas para medir la toxicidad, entre otros. El artículo pone a disposición la caja de herramientas desarrolladas durante la investigación, las que pueden ser de utilidad para trabajar corpus de texto de gran magnitud.
Descargas
Citas
Ain, Q. T., Ali, M., Riaz, A., Noureen, A., Kamran, M., Hayat, B., & Rehman, A. (2017). Sentiment Analysis Using Deep Learning Techniques: A Review. International Journal of Advanced Computer Science and Applications, 8(6). https://doi.org/10.14569/IJACSA.2017.080657
Angelov, D. (2020). Top2vec: Distributed Representations of Topics. arXiv preprint arXiv:2008.09470. https://doi.org/10.48550/arXiv.2008.09470
Ansolabehere, S. & Iyengar, S. (1994). Riding the wave and claiming ownership over issues: The joint effects of advertising and news coverage in campaigns. Public Opinion Quarterly, 58(3), 335-357. https://doi.org/10.1086/269431
Arcila Calderón, C., Van Atteveldt, W., & Trilling, D. (2021). Métodos Computacionales y Big Data en la Investigación en Comunicación: Editorial Dossier (Special Issue Computational Methods and Big Data in Communication Research ). Cuadernos.Info, (49), I-IV.
Aruguete, N. (2015). El poder de la agenda: política, medios y público (The power of the agenda: politics, media, and public). Biblos.
Bast, J. (2021). Managing the Image. The Visual Communication Strategy of European Right- Wing Populist Politicians on Instagram. Journal of Political Marketing. https://doi.org/10.1080/15377857.2021.1892901
Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer. https://link.springer.com/book/9780387310732
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993-1022.https://jmlr.org/papers/v3/blei03a.html
Bossetta, M. (2018). The Digital Architectures of Social Media: Comparing Political Campaigning on Facebook, Twitter, Instagram, and Snapchat in the 2016 US Election. Journalism & Mass Communication Quarterly, 95(2), 471-496. https://doi.org/10.1177/1077699018763307
Calvo, E. (2015). Anatomía política de Twitter en Argentina. Tuiteando #Nisman (Political anatomy of Twitter in Argentina. Tweeting #Nisman). Capital Intelectual.
Calvo, E. & Aruguete, N. (2020). Fake news, trolls y otros encantos: Cómo funcionan (para bien y para mal) las redes sociales (Fake news, trolls, and other charms: How do social networks work (for better and for worse)). Siglo XXI Editores.
Cárdenas, A. (2020). Uso de Twitter como estrategia de comunicación política en campañas presidenciales (México, Colombia y Perú 2012-2016). Razón y Palabra, 24, (109). https://doi.org/10.26807/rp.v24i109.1716
Chadwick, A., Dennis, J., & Smith, A. P. (2015). Politics in the Age of Hybrid Media: Power, Systems, and Media Logics. In A. Bruns, G. Enli, E. Skogerbø, A. O. Larsson, & C. Christensen, The Routledge Companion to Social Media and Politics (pp. 7-22). Routledge.
Enli, G. S. & Skogerbø, E. (2013). Personalized campaigns in party-centred politics. Twitter and Facebook as arenas for political communication. Information, Communication & Society, 16(5), 757-774. https://doi.org/10.1080/1369118X.2013.782330
Figuereo-Benítez, J. C., González-Quiñones, F., & Machin-Mastromatteo, J. D. (2021). Instagram como objeto de estudio en investigaciones recientes. Una revisión de literatura con enfoque en revistas científicas (Instagram as an object of study in recent research. A literature review with a focus on scientific journals). Ámbitos: Revista internacional de comunicación, 53, 9-23. https://doi.org/10.12795/Ambitos.2021.i53.01
Flores-Márquez, D. & González Reyes, R. (2021). En busca de coordenadas metodológicas para estudiar la cultura digital (In search of methodological coordinates to study digital culture). In D. Flores-Márquez & R. González Reyes (Coords), La imaginación metodológica. Coordenadas, rutas y apuestas para el estudio de la cultura digital (The methodological imagination. Coordinates, routes, and stakes for the study of digital culture) (pp. 15-23). Tintable.
Fortuna, P., Soler, J., & Wanner, L. (2020, May). Toxic, Hateful, Offensive or Abusive? What Are We Really Classifying? An Empirical Analysis of Hate Speech Datasets. In Proceedings of the Twelfth Language Resources and Evaluation Conference (pp. 6786-6794). European Language Resources Association. https://aclanthology.org/2020.lrec-1.838
Garimella, K., Morales, G. D. F., Gionis, A., & Mathioudakis, M. (2018). Quantifying Controversy on Social Media. ACM Transactions on Social Computing, 1(1), 1-27. https://doi.org/10.1145/3140565
González-Bustamante, B. (2015). Evaluando Twitter como indicador de opinión pública: una mirada al arribo de Bachelet a la presidencial chilena 2013 (Assessing Twitter as an indicator of public opinion: a look at Bachelet’s arrival to the Chilean presidential election in 2013). Revista SAAP, 9(1), 119-141. https://revista.saap.org.ar/articulos/revista-saap-volumen-9-1.html
Gruzd, A., Lannigan, J., & Quigley, K. (2018). Examining government cross-platform engagement in social media: Instagram vs Twitter and the big lift project. Government Information Quarterly, 35(4), 579-587. https://doi.org/10.1016/j.giq.2018.09.005
Gusfield, J. R. (2014). La cultura de los problemas públicos: el mito del conductor alcoholizado versus la sociedad inocente (The culture of public problems: the myth of the drunk driver versus the innocent society). Siglo XXI Editores.
Hasebrink, U. & Hepp, A. (2017). How to research cross-media practices? Investigating media repertoires and media ensembles. Convergence: The International Journal of Research into New Media Technologies, 23(4), 362-377. https://doi.org/10.1177/1354856517700384
Hodges, J. L. (1958). The significance probability of the smirnov two-sample test. Arkiv för Matematik, 3(5), 469-486. https://doi.org/10.1007/bf02589501
Hua, Y., Ristenpart, T., & Naaman, M. (2020). Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections. Proceedings of the International AAAI Conference on Web and Social Media, 14(1), 272-282. https://doi.org/10.1609/icwsm.v14i1.7298
Iyengar, S. (1990). The accessibility bias in politics: Television news and public opinion. International Journal of Public Opinion Research, 2(1), 1-15.
Jaidka, K., Guntuku, S., & Ungar, L. (2018, June). Facebook versus Twitter: Differences in self-disclosure and trait prediction. Proceedings of the International AAAI Conference on Web and Social Media, 12(1). https://doi.org/10.1609/icwsm.v12i1.15026
Kaplan, N., Park, D. K., & Ridout, T. N. (2006). Dialogue in American Political Campaigns? An Examination of Issue Convergence in Candidate Television Advertising. American Journal of Political Science, 50(3), 724-736. https://doi.org/10.1111/j.1540-5907.2006.00212.x
Karlsen, R. & Enjolras, B. (2016). Styles of Social Media Campaigning and Influence in a Hybrid Political Communication System: Linking Candidate Survey Data with Twitter Data. The International Journal of Press/Politics, 21(3), 338-357. https://doi.org/10.1177/1940161216645335
Kelley, S. & Mirer, T. W. (1974). The Simple Act of Voting. American Political Science Review, 68(2), 572-591. https://doi.org/10.2307/1959506
Larsson, A. O. (2015). Green light for interaction: Party use of social media during the 2014 Swedish election year. First Monday, 20(1). https://doi.org/10.5210/fm.v20i12.5966
LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., & Jackel, L. D. (1989). Backpropagation applied to handwritten zip code recognition. Neural Computation, 1(4), 541-551. https://doi.org/10.1162/neco.1989.1.4.541
López-López, P. C. & Vásquez-González, J. (2018). Agenda temática y Twitter: elecciones presidenciales en América Latina durante el período 2015-2017 (Thematic agenda and Twitter: Presidential elections in Latin America during the 2015-2017 period). Profesional De La Información, 27(6), 1204-1214. https://doi.org/10.3145/epi.2018.nov.04
Manning, C. & Schütze, H. (1999). Foundations of Statistical Natural Language Processing. MIT Press.
Martin, J. R. & White, P. R. R. (2005). The Language of Evaluation. Appraisal in English. Palgrave Macmillan.
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology, 27, 415-444. https://doi.org/10.1146/annurev.soc.27.1.415
Müller, A. C. & Guido, S. (2016). Introduction to Machine Learning with Python. A Guide for Data Scientists.
O'Reilly Media, Inc. Nielsen, R. K. & Schrøder, K. C. (2014). The Relative Importance of Social Media for Accessing, Finding, and Engaging with News. An eight-country cross-media comparison. Digital Journalism, 2(4), 472-489. https://doi.org/10.1080/21670811.2013.872420
Owen, D. (2017). New Media and Political Campaigns. In K. Kensi & K. Hall Jamieson (Eds.), The Oxford Handbook of Political Communication (pp. 829-836). https://doi.org/10.1093/ oxfordhb/9780199793471.013.016
Paulino, F. O. & Waisbord, S. (2021). Las narrativas del populismo reaccionario: Bolsonaro en Twitter durante la pandemia (The narratives of reactionary populism: Bolsonaro on Twitter during the pandemic). Mediapolis–Revista de Comunicação, Jornalismo e Espaço Público, (12), 33-48. https://doi.org/10.14195/2183-6019_12_2
Petrocik, J. R. (1996). Issue Ownership in Presidential Elections, with a 1980 Case Study. American Journal of Political Science, 40(3), 825-850. https://doi.org/10.2307/2111797
Prada Espinel, Ó. A. & Romero Rodríguez, L. M. (2018). Polarización y demonización en la campaña presidencial de Colombia de 2018: análisis del comportamiento comunicacional en el Twitter de Gustavo Petro e Iván Duque (Polarization and Demonization in the 2018 Presidential Campaign of Colombia: Analysis of Twitter’s Communication Behavior by Gustavo Petro and Iván Duque). Revista Humanidades, 9(1). https://doi.org/10.15517/h.v9i1.35343
Quevedo, L. A., & Ramírez, I. (2022). Polarizados ¿Por qué preferimos la grieta?(Aunque digamos lo contrario). Revista SAAP, 16(1), 220-222.
Röder, M., Both, A., & Hinneburg, A. (2015). Exploring the Space of Topic Coherence Measures. In X. Cheng & H. Li (Chairs), WSDM’15: Proceedings of the Eighth ACM International Conference on Web Search and Data Mining (pp. 399-408). https://doi.org/10.1145/2684822.2685324
Rogers, R. (2017). Digital Methods for Cross-Platform Analysis. In J. Burgess, A. Marwick, & T. Poell, The SAGE Handbook of Social Media (pp. 91-110). SAGE. https://doi.org/10.4135/9781473984066
Salgado Andrade, E. (2013). Twitter en la campaña electoral de 2012 (Twitter in the Electora Campaign of 2012). Desacatos, (42), 217-232. https://doi.org/10.29340/42.78
Scheufele, D. A. (2000). Agenda-Setting, Priming, and Framing Revisited: Another Look at Cognitive Effects of Political Communication. Mass Communication & Society, 3(2-3), 297-316. https://doi.org/10.4324/9781315679402-5
Scheufele, D. A. & Iyengar, S. (2012). The State of Framing Research: A Call for New Directions. In K. Kenski & K. Hall Jamieson (Eds.), The Oxford Handbook of Political Communication Theories (pp. 1-26). https://doi.org/10.1093/oxfordhb/9780199793471.013.47
Spierings, N. & Jacobs, K. (2019). Political parties and social media campaigning. Acta Politica, 54(1), 145-173. https://doi.org/10.1057/s41269-018-0079-z
Stier, S., Bleier, A., Lietz, H., & Strohmaier, M. (2018). Election Campaigning on Social Media: Politicians, Audiences, and the Mediation of Political Communication on Facebook and Twitter. Political Communication, 35(1), 50-74. https://doi.org/10.1080/10584609.2017.1334728
Thelwall, M. (2017). The Heart and Soul of the Web? Sentiment Strength Detection in the Social Web with SentiStrength. In J. Holyst (Ed.), Cyberemotions. Understanding Complex Systems (pp. 119-134). Springer. https://doi.org/10.1007/978-3-319-43639-5_7
Thorhauge, A. M. & Lomborg, S. (2016). Cross-media communication in context: A mixedmethods approach. MedieKultur: Journal of Media and Communication Research, 32(60), 16. https://doi.org/10.7146/mediekultur.v32i60.22090
Wulczyn, E., Thain, N., & Dixon, L. (2017). Ex Machina: Personal Attacks Seen at Scale. In R. Barret & R. Cummings (Chairs), WWW’ 17: Proceedings of the 26th International Conference on World Wide Web (pp. 1391–1399). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3038912.3052591
Zwillinger, D. & Kokoska, S (2000). CRC Standard Probability and Statistics Tables and Formulae. Champan & Hall.
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2023 Cuadernos.info
![Creative Commons License](http://i.creativecommons.org/l/by-sa/4.0/88x31.png)
Esta obra está bajo una licencia internacional Creative Commons Atribución-CompartirIgual 4.0.