Quantifying echo chamber effects in information spreading over political communication networks

Publication date

2026-02-23T08:42:03Z

2026-02-23T08:42:03Z

2019

2026-02-23T08:42:03Z



Abstract

Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects of echo chambers in information spreading phenomena over political communication networks. Mining 12 million Twitter messages, we reconstruct a network in which users interchange opinions related to the impeachment of the former Brazilian President Dilma Rousseff. We define a continuous political leaning parameter, independent of the network's structure, that allows to quantify the presence of echo chambers in the strongly connected component of the network. These are reflected in two well-separated communities of similar sizes with opposite views of the impeachment process. By means of simple spreading models, we show that the capability of users in propagating the content they produce, measured by the associated spreading capacity, strongly depends on their attitude. Users expressing pro-impeachment leanings are capable to transmit information, on average, to a larger audience than users expressing anti-impeachment leanings. Furthermore, the users' spreading capacity is correlated to the diversity, in terms of political position, of the audience reached. Our method can be exploited to identify the presence of echo chambers and their effects across different contexts and shed light upon the mechanisms allowing to break echo chambers.


We thank Gino Ceotto and Diogo H. Silva for useful discussion. This work was partially supported by the Brazilian agencies CNPq and FAPEMIG. Authors thank the support from the program Ciência sem Fronteiras'CAPES under project No. 88881.030375/2013-01. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior'Brasil (CAPES)'Finance Code 001. MS acknowledges financial support by the J. McDonnell Foundation. RP-S acknowledges financial support from the Spanish MINECO, under Project No. FIS2016-76830-C2-1-P, and additional financial support from ICREA Academia, funded by the Generalitat de Catalunya.

Document Type

Article


Published version

Language

English

Publisher

Springer

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EPJ Data Science. 2019;8(1):35

info:eu-repo/grantAgreement/ES/1PE/FIS2016-76830-C2-1-P

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