https://doi.org/10.1140/epjds/s13688-022-00360-8
Regular Article
News sharing on Twitter reveals emergent fragmentation of media agenda and persistent polarization
1
Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Av. Cantilo s/n, C1428EGA, Ciudad Autónoma de Buenos Aires, Argentina
2
Instituto del Cálculo (IC), UBA-CONICET, Intendente Güiraldes 2160, C1428EGA, Ciudad Autónoma de Buenos Aires, Argentina
3
Instituto de Física de Buenos Aires (IFIBA), CONICET, Av. Cantilo s/n, C1428EGA, Ciudad Autónoma de Buenos Aires, Argentina
4
Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Diagonal Las Torres 2640, 7910000, Santiago, Chile
Received:
29
December
2021
Accepted:
1
August
2022
Published online:
19
August
2022
News sharing on social networks reveals how information disseminates among users. This process, constrained by user preferences and social ties, plays a key role in the formation of public opinion. In this work, we used bipartite news-user networks to study the news sharing behavior of main Argentinian media outlets in Twitter. Our objective was to understand the role of political polarization in the emergence of high affinity groups with respect to news sharing. We compared results between years with and without presidential elections, and between groups of politically active and inactive users, the latter serving as a control group. The behavior of users resulted in well-differentiated communities of news articles identified by a unique distribution of media outlets. In particular, the structure of these communities revealed the dominant ideological polarization in Argentina. We also found that users formed two groups identified by their consumption of media outlets, which also displayed a bias towards the two main parties that dominate the political life in Argentina. Overall, our results consistently identified ideological polarization as a main driving force underlying Argentinian news sharing behavior in Twitter.
Key words: Complex networks / Social media / News consumption / Natural language processing
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1140/epjds/s13688-022-00360-8.
© The Author(s) 2022
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