Twitter, neighboring Internet users and the local interstices of political polarization: A study focused on the 2019 electoral campaign in the Party of General Pueyrredón, Argentina
Twitter, internautas vecinos y los intersticios de la polarización política: Un estudio centrado en la campaña electoral de 2019 en el Partido de General Pueyrredón, Argentina
Twitter, internautas vizinhos e os interstícios locais da polarização política: Um estudo focado na campanha eleitoral de 2019 no Partido do General Pueyrredón, Argentina
| 2021 | |
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virtual public sphere electoral campaigns digital sociology subnational esfera pública virtual campañas electorales sociología digital subnacional esfera pública virtual campanhas eleitorais sociologia digital subnacional |
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| Español | |
| Universidad ORT Uruguay | |
| RAD | |
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https://revistas.ort.edu.uy/inmediaciones-de-la-comunicacion/article/view/3163
http://hdl.handle.net/20.500.11968/4330 |
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| Acceso abierto | |
| http://creativecommons.org/licenses/by/4.0 |
| Sumario: | Social networks show that the virtual public space can be deconstructed in a multiplicity of spheres. For some readings, that fragmentation encourages polarization and reproduces the so-called echo chambers. From other perspectives, the overlapping of audiences is what enables the circulation of messages. Following this last line, the article focuses on a specific analysis, focused on Internet users who followed the candidates for Mayor in the General Pueyrredón Party (Argentina) on Twitter during the 2019 electoral campaign. From there, we propose to open some lines of reflection about the debate on the limitations or democratic capacities of virtual public space. Our hypothesis is that there is a local virtual public space populated by a type of users –which we call neighboring Internet users– that can be thought of as a kind of sub-national interstice within the framework of the prevailing political polarization at the country level. For the follow-up and analysis of the Internet users, the R software was used. Firstly, we reconstructed the corpus of followers by creating a database that allows us to identify neighborhoods and distances on the political map. Secondly, we visualized and analyzed the most frequent words in the biographies of the political candidates followers. |
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