We present a project investigating the impact of social media on ideological structuring of political attitudes in a generational perspective, with Italy (around the 2024 European Parliament elections) as a case study. We introduce an innovative mixed-methods, sequential, quantitative-driven, multi-stage design combining surveys, qualitative interviews, and social media data, which effectively integrates qualitative and quantitative components to analyze the effect of social media influencers on political attitudes across generations. We present project design along with interaction and integration among components (methodological innovations include a “Swipe” module for respondents–influencers linkage and use of AI for classifying social media posts). We describe individual components (including first empirical results), an intermediate convergent assessment stage, and directions for data analysis.
De Sio, L., Legnante, G., Tuorto, D., Vezzoni, C., Boldrini, M., Bordignon, M., et al. (2026). Assessing public sphere influence on political attitudes across generations: a mixed-methods study of generational political structuring in Italy. FRONTIERS IN POLITICAL SCIENCE, 8, 1-14 [10.3389/fpos.2026.1720542].
Assessing public sphere influence on political attitudes across generations: a mixed-methods study of generational political structuring in Italy
Tuorto, Dario;Boldrini, Matteo
;Maggini, Nicola;Piacentini, Arianna;
2026
Abstract
We present a project investigating the impact of social media on ideological structuring of political attitudes in a generational perspective, with Italy (around the 2024 European Parliament elections) as a case study. We introduce an innovative mixed-methods, sequential, quantitative-driven, multi-stage design combining surveys, qualitative interviews, and social media data, which effectively integrates qualitative and quantitative components to analyze the effect of social media influencers on political attitudes across generations. We present project design along with interaction and integration among components (methodological innovations include a “Swipe” module for respondents–influencers linkage and use of AI for classifying social media posts). We describe individual components (including first empirical results), an intermediate convergent assessment stage, and directions for data analysis.| File | Dimensione | Formato | |
|---|---|---|---|
|
fpos-8-1720542.pdf
accesso aperto
Tipo:
Versione (PDF) editoriale / Version Of Record
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione
1.61 MB
Formato
Adobe PDF
|
1.61 MB | Adobe PDF | Visualizza/Apri |
|
data sheet 1.docx
accesso aperto
Tipo:
File Supplementare
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione
749.69 kB
Formato
Microsoft Word XML
|
749.69 kB | Microsoft Word XML | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


