期刊论文详细信息
EPJ Data Science
Evolution of the political opinion landscape during electoral periods
Dimitris Kotzinos1  Tomás Mussi Reyero2  Mariano G. Beiró3  J. Ignacio Alvarez-Hamelin3  Laura Hernández4 
[1] ETIS UMR-8051 CY Cergy Paris Université, ENSEA, CNRS, 2 Av. Adolphe Chauvin, 95302, Cedex, France;Facultad de Ingeniería, Universidad de Buenos Aires, Paseo Colón 850, C1063ACV, Buenos Aires, Argentina;Facultad de Ingeniería, Universidad de Buenos Aires, Paseo Colón 850, C1063ACV, Buenos Aires, Argentina;CONICET – Universidad de Buenos Aires. INTECIN, Paseo Colón 850, C1063ACV, Buenos Aires, Argentina;Laboratoire de Physique Théorique et Modélisation, UMR-8089 CNRS, CY Cergy Paris Université, 2 Av. Adolphe Chauvin, 95302, Cedex, France;
关键词: Social media;    Elections;    Opinion modelling;    Twitter data;   
DOI  :  10.1140/epjds/s13688-021-00285-8
来源: Springer
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【 摘 要 】

We present a study of the evolution of the political landscape during the 2015 and 2019 presidential elections in Argentina, based on data obtained from the micro-blogging platform Twitter. We build a semantic network based on the hashtags used by all the users following at least one of the main candidates. With this network we can detect the topics that are discussed in the society. At a difference with most studies of opinion on social media, we do not choose the topics a priori, they emerge from the community structure of the semantic network instead. We assign to each user a dynamical topic vector which measures the evolution of her/his opinion in this space and allows us to monitor the similarities and differences among groups of supporters of different candidates. Our results show that the method is able to detect the dynamics of formation of opinion on different topics and, in particular, it can capture the reshaping of the political opinion landscape which has led to the inversion of result between the two rounds of 2015 election.

【 授权许可】

CC BY   

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