Abstract
On October 17, 1945, a vast popular mobilization marched over the Plaza de Mayo to demand for the release of Juan Domingo Perón. Since then, that day has been considered the origin of Peronismo [Peronism], one of the most significant political movements in Argentine history. The commemoration of that event, which later came to be called Día de la Lealtad [Loyalty Day] was modified over time by the peronistas [Peronist], and motivated a variety of historical analyses. Our aim is to expand this series by incorporating the narratives of memory that circulate on Twitter. We analyze a corpus of tweets published between 2009 and 2020. The first of these dates is marked by the availability of the archive of this social media through the Twitter Academic API (v2). The second one, a decade later, refers to when, in the context of the COVID-19 pandemic, some Peronist groups organized the first virtual mobilization to commemorate the Día de la Lealtad [Loyalty Day], even though digitization of the event had a previous history.
To study the process by which arguments that elaborate past-present relations on Twitter are constructed and interpreted, we use and evaluate some widely spread tools and techniques for the analysis of the Twittersphere. These include analyzing the changes in the volume of tweets by year; identifying hashtags that articulate narratives for and against the commemoration; tracking relevant users for each conversation; studying the circulation of information with the aid of graph networks and analyzing tweet content through distant reading.
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Notes
- 1.
The official announcement regarding the end of the free access to Twitter’s API can be found here https://twitter.com/TwitterDev/status/1621026986784337922
- 2.
Over the past years, Visual Network Analysis has become a research field in its own terms. We cannot provide a detailed discussion about this matter here, but a comprehensive analysis of its particularities and strengths, as well of its nuances and biases, can be found on Jacomy (2021).
- 3.
The syntax of that initial query was as follows: “#17O OR #lealtad OR #vivaperón OR #17deoctubre OR #felizdiadelalealtad OR #diadelalealtadperonista OR #diadelalealtad OR #lealtadperonista OR #17oct.”
- 4.
The final query can be found here: https://bit.ly/October17Query
- 5.
These are the pairs that follow according to their magnitude of repetition: #DiaDeLaLealtad-#75Octubres (22,794), #DiaDeLaLealtad-#17DeOctubre (20,840), #17DeOctubre-#DiaDeLaLealtadPeronista (12,922), and #17DeOctubre-#75OctubresDeLealtad (10,876).
- 6.
The pair was followed by #17ODiaDeLaCorrupcion-#17DeOctubre (2376), #17ODiaDeLaCorrupcion-#DiaDeLaLealtad (2.311), and #17ODiaDeLaCorrupcion-#75Octubres (1946).
- 7.
These 5777 hashtags were used 567,012 times, at a rate of 98 uses each. The average is misleading, since the use of hashtags, like retweeting, follows the dynamics of long-tailed distribution phenomena. The top decile of hashtags averages 954 uses/hashtag, while the rest barely reach 3.3 uses on average.
References
Acha, O. (2019). La Argentina peronista: una historia desde abajo (1945–1955). Red Editorial.
Barberá, P., Jost, J. T., Nagler, J., Tucker, J. A., & Bonneau, R. (2015). Tweeting from left to right: Is online political communication more than an Echo chamber? Psychological Science OnlineFirst, 26(10), 1531.
Bell, C. (1992). Ritual theory. Oxford University Press.
Boullier, D. (2015). Les sciences sociales face aux traces du big data. Société, opinion ou vibrations? Revue française de science politique, 65(5–6), 805–828.
Burgess, J., & Baym, N. K. (2020). Twitter: A biography. NYU Press.
Burgess, J., Galloway, A., & Sauter, T. (2015). Hashtag as hybrid forum: The case of #agchatoz. In N. Rambukkana (Ed.), Hashtag publics: The power and politics of discursive networks (pp. 61–76). Peter Lang.
Bruns, A., & Burgess, J. (2015). The use of twitter hashtags in the formation of ad hoc publics. In N. Rambukkana (Ed.), Hashtag publics. The power and politics of discursive networks (pp. 13–27). Peter Lang.
Calvo, E., & Aruguete, N. (2020). Fake news, trolls y otros encantos: Cómo funcionan (para bien y para mal) las redes sociales. Siglo XXI Editores.
Clavert, F. (2021). History in the era of massive data. Geschichte und Gesellschaft, 47(1), 175–194.
Devoto, F. (2014). Conmemoraciones poliédricas: Acerca del primer centenario en la Argentina. In N. Pagano & M. Martínez (Eds.), Conmemoraciones, patrimonio y usos del pasado: La elaboración social de la experiencia histórica. Miño y Dávila Editores.
Ehrlich, L. (2022). La reinvención del peronismo (1955–1965). Universidad Nacional de Quilmes Editorial.
Figueroa Muñoz, L. A. A. (2020). Pensar los lugares de memoria: El uso del hashtag en Twitter. Revista pueblos y fronteras digital, 15, 1.
Fussey, P., & Roth, S. (2020). Digitizing sociology: Continuity and change in the internet era. Sociology, 54(4), 659–674.
Grimson, A. (2019). ¿Qué es el peronismo? Siglo XXI.
Gualda, E., Borrero, J. D., & Carpio Cañada, J. (2015). La “Spanish Revolution” en Twitter (2): Redes de hashtags (#) y actores individuales y colectivos respecto a los desahucios en España. Redes. Revista hispana para el análisis de redes sociales, 26(1), 1.
Hoskins, A. (2017). Digital memory studies: Media pasts in transition. Routledge.
Jacomy, M. (2021). Situating visual network analysis. Aalborg Universitetsforlag.
Koselleck, R. (1993). Futuro pasado: Para una semántica de los tiempos históricos. Ed. Paidós.
La Rocca, G., & Boccia Artieri, G. (2023). Interpreting the changeable meaning of hashtags: Toward the theorization of a model. Frontiers in Sociology, 7.
Moretti, F. (2016). Lectura distante. FCE - Fondo de Cultura Económica.
Morstatter, F., Pfeffer, J., & otros (2013). Is the sample good enough? Comparing Data from Twitter’s Streaming API with Twitter’s Firehose.
Neiburg, F. (1992). O 17 de outubro na Argentina: espaço e formação social do carisma. Revista Brasileria de Ciências Sociais, 20, 70–89.
Noiret, S. (2018). Trabajar con el pasado en internet: La historia pública digital y las narraciones de las redes sociales. Ayer, 110, 111–140.
Pariser, E. (2017). El filtro burbuja: Cómo la web decide lo que leemos y lo que pensamos. Penguin Random House Grupo Editorial España.
Plotkin, M. (2002). Mañana es San Perón. A cultural history of Perón’s Argentina. SR Books.
Reguillo, R. (2017). Paisajes insurrectos. Jóvenes, redes y revueltas en el otoño civilizatorio. Nuevos emprendimientos editoriales.
Rogers, R. (2013). Debanalizing twitter: The transformation of an object of study. In Proceedings of the 3rd annual ACM web science conference, WebSci 2013.
Smyth, H., & Echavarria, D. R. (2021). Twitter and feminist commemoration of the 1916 Easter rising. Journal of Digital History, 1(1), 142–167.
Sumikawa, Y., & Jatowt, A. (2021). Analyzing history-related posts in twitter. International Journal on Digital Libraries, 22(1), 105–134.
Tromble, R. (2021). Where have all the data gone? A critical reflection on academic digital research in the post-API age. Social media + Society, 7(1).
Van Dijck, J. (2016). La cultura de la conectividad: Una historia crítica de las redes sociales. Siglo XXI Editores.
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Ferreyra, S., Quiroga, N., Cordeu, J.R. (2023). Narratives of Memory on Twitter: The Case of the Día de la Lealtad [Loyalty Day] in Argentina. In: Pocecco, A., Gualda, E., Mangone, E. (eds) Collective Memory Narratives in Contemporary Culture. Springer, Cham. https://doi.org/10.1007/978-3-031-41921-8_8
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