Networked partisanship and framing: a socio-semantic network analysis of the Italian debate on migration
Tommaso Radicioni, Tiziano Squartini, Elena Pavan, Fabio Saracco

TL;DR
This study analyzes Italian Twitter debates on migration from May to November 2019, revealing complex partisan dynamics and framing practices through socio-semantic network analysis without external data.
Contribution
It introduces a novel socio-semantic network methodology to detect partisan communities and analyze framing dynamics solely from social media data.
Findings
Identified distinct partisan communities with different migration framing.
Revealed core-periphery hashtag network structure.
Detected shifting political alliances within the debate.
Abstract
The huge amount of data made available by the massive usage of social media has opened up the unprecedented possibility to carry out a data-driven study of political processes. While particular attention has been paid to phenomena like elite and mass polarization during online debates and echo-chambers formation, the interplay between online partisanship and framing practices, jointly sustaining adversarial dynamics, still remains overlooked. With the present paper, we carry out a socio-semantic analysis of the debate about migration policies observed on the Italian Twittersphere, across the period May-November 2019. As regards the social analysis, our methodology allows us to extract relevant information about the political orientation of the communities of users - hereby called partisan communities - without resorting upon any external information. Remarkably, our community detection…
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