Analysing Twitter semantic networks: the case of 2018 Italian elections

Abstract Social media play a key role in shaping citizens’ political opinion. According to the Eurobarometer, the percentage of EU citizens employing online social networks on a daily basis has increased from 18% in 2010 to 48% in 2019. The entwinement between social media and the unfolding of polit...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Tommaso Radicioni, Fabio Saracco, Elena Pavan, Tiziano Squartini
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a1e6310a49e04c9c94e9d4d05c9512b9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:a1e6310a49e04c9c94e9d4d05c9512b9
record_format	dspace
spelling	oai:doaj.org-article:a1e6310a49e04c9c94e9d4d05c9512b92021-12-02T16:06:10ZAnalysing Twitter semantic networks: the case of 2018 Italian elections10.1038/s41598-021-92337-22045-2322https://doaj.org/article/a1e6310a49e04c9c94e9d4d05c9512b92021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92337-2https://doaj.org/toc/2045-2322Abstract Social media play a key role in shaping citizens’ political opinion. According to the Eurobarometer, the percentage of EU citizens employing online social networks on a daily basis has increased from 18% in 2010 to 48% in 2019. The entwinement between social media and the unfolding of political dynamics has motivated the interest of researchers for the analysis of users online behavior—with particular emphasis on group polarization during debates and echo-chambers formation. In this context, semantic aspects have remained largely under-explored. In this paper, we aim at filling this gap by adopting a two-steps approach. First, we identify the discursive communities animating the political debate in the run up of the 2018 Italian Elections as groups of users with a significantly-similar retweeting behavior. Second, we study the mechanisms that shape their internal discussions by monitoring, on a daily basis, the structural evolution of the semantic networks they induce. Above and beyond specifying the semantic peculiarities of the Italian electoral competition, our approach innovates studies of online political discussions in two main ways. On the one hand, it grounds semantic analysis within users’ behaviors by implementing a method, rooted in statistical theory, that guarantees that our inference of socio-semantic structures is not biased by any unsupported assumption about missing information; on the other, it is completely automated as it does not rest upon any manual labelling (either based on the users’ features or on their sharing patterns). These elements make our method applicable to any Twitter discussion regardless of the language or the topic addressed.Tommaso RadicioniFabio SaraccoElena PavanTiziano SquartiniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-22 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Tommaso Radicioni Fabio Saracco Elena Pavan Tiziano Squartini Analysing Twitter semantic networks: the case of 2018 Italian elections
description	Abstract Social media play a key role in shaping citizens’ political opinion. According to the Eurobarometer, the percentage of EU citizens employing online social networks on a daily basis has increased from 18% in 2010 to 48% in 2019. The entwinement between social media and the unfolding of political dynamics has motivated the interest of researchers for the analysis of users online behavior—with particular emphasis on group polarization during debates and echo-chambers formation. In this context, semantic aspects have remained largely under-explored. In this paper, we aim at filling this gap by adopting a two-steps approach. First, we identify the discursive communities animating the political debate in the run up of the 2018 Italian Elections as groups of users with a significantly-similar retweeting behavior. Second, we study the mechanisms that shape their internal discussions by monitoring, on a daily basis, the structural evolution of the semantic networks they induce. Above and beyond specifying the semantic peculiarities of the Italian electoral competition, our approach innovates studies of online political discussions in two main ways. On the one hand, it grounds semantic analysis within users’ behaviors by implementing a method, rooted in statistical theory, that guarantees that our inference of socio-semantic structures is not biased by any unsupported assumption about missing information; on the other, it is completely automated as it does not rest upon any manual labelling (either based on the users’ features or on their sharing patterns). These elements make our method applicable to any Twitter discussion regardless of the language or the topic addressed.
format	article
author	Tommaso Radicioni Fabio Saracco Elena Pavan Tiziano Squartini
author_facet	Tommaso Radicioni Fabio Saracco Elena Pavan Tiziano Squartini
author_sort	Tommaso Radicioni
title	Analysing Twitter semantic networks: the case of 2018 Italian elections
title_short	Analysing Twitter semantic networks: the case of 2018 Italian elections
title_full	Analysing Twitter semantic networks: the case of 2018 Italian elections
title_fullStr	Analysing Twitter semantic networks: the case of 2018 Italian elections
title_full_unstemmed	Analysing Twitter semantic networks: the case of 2018 Italian elections
title_sort	analysing twitter semantic networks: the case of 2018 italian elections
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a1e6310a49e04c9c94e9d4d05c9512b9
work_keys_str_mv	AT tommasoradicioni analysingtwittersemanticnetworksthecaseof2018italianelections AT fabiosaracco analysingtwittersemanticnetworksthecaseof2018italianelections AT elenapavan analysingtwittersemanticnetworksthecaseof2018italianelections AT tizianosquartini analysingtwittersemanticnetworksthecaseof2018italianelections
_version_	1718385107073499136

Analysing Twitter semantic networks: the case of 2018 Italian elections

Ejemplares similares