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Autores principales: Perrier, Rémi, Hernández, Laura, Alvarez-Hamelin, J. Ignacio, Kotzinos, Mariano G. Beiró Dimitris
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2503.05552
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author Perrier, Rémi
Hernández, Laura
Alvarez-Hamelin, J. Ignacio
Kotzinos, Mariano G. Beiró Dimitris
author_facet Perrier, Rémi
Hernández, Laura
Alvarez-Hamelin, J. Ignacio
Kotzinos, Mariano G. Beiró Dimitris
contents We present an analysis of the dynamics of discussions in Twitter (before it became X) among supporters of various candidates in the 2022 French presidential election, and followers of different types of media. Our study demonstrates that we can automatically detect the synchronization of interest among different groups around specific topics at particular times. We introduce two complementary methods for constructing dynamic semantic networks, each with its own advantages. The growing aggregated network helps identify the reactivation of past topics, while the rolling window network is more sensitive to emerging discussions that, despite their significance, may appear suddenly and have a short lifespan. These two approaches offer distinct perspectives on the discussion landscape. Rather than choosing between them, we advocate for using both, as their comparison provides valuable insights at a relatively low computational and storage cost. Our findings confirm and quantify, on a larger scale and in an automatic, agnostic manner, observations previously made using more qualitative methods. We believed this work represents a step forward in developing methodologies to assess equity in information treatment, an obligation imposed by law on broadcasters that use broadcast spectrum frequencies in certain countries.
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publishDate 2025
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spellingShingle Synchronization between media followers and political supporters during an election process: towards a real time study
Perrier, Rémi
Hernández, Laura
Alvarez-Hamelin, J. Ignacio
Kotzinos, Mariano G. Beiró Dimitris
Social and Information Networks
Computers and Society
We present an analysis of the dynamics of discussions in Twitter (before it became X) among supporters of various candidates in the 2022 French presidential election, and followers of different types of media. Our study demonstrates that we can automatically detect the synchronization of interest among different groups around specific topics at particular times. We introduce two complementary methods for constructing dynamic semantic networks, each with its own advantages. The growing aggregated network helps identify the reactivation of past topics, while the rolling window network is more sensitive to emerging discussions that, despite their significance, may appear suddenly and have a short lifespan. These two approaches offer distinct perspectives on the discussion landscape. Rather than choosing between them, we advocate for using both, as their comparison provides valuable insights at a relatively low computational and storage cost. Our findings confirm and quantify, on a larger scale and in an automatic, agnostic manner, observations previously made using more qualitative methods. We believed this work represents a step forward in developing methodologies to assess equity in information treatment, an obligation imposed by law on broadcasters that use broadcast spectrum frequencies in certain countries.
title Synchronization between media followers and political supporters during an election process: towards a real time study
topic Social and Information Networks
Computers and Society
url https://arxiv.org/abs/2503.05552