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Polarization and Networked Framing

Authors: Sercan Kiyak; Stefan Mertens; David De Coninck; Leen d'Haenens;

Polarization and Networked Framing

Abstract

This exploratory study adopts a mixed-methods approach to examine the dynamics of political communication during refugee crises in German-language X (formerly Twitter), focusing on the Syrian and Ukrainian refugee influxes of September 2015 and March 2022. Using the X API, we collected 551,873 tweets related to the Syrian crisis and 236,034 tweets related to the Ukrainian crisis. The retweet networks associated with both crises were segmented into attitudinal communities by labeling them based on their position toward refugees. These networks were analyzed for polarization, community interactions and activity, influential users, and the dynamic networked framing of the crises. Our social network analysis highlighted that the online anti-refugee community exhibited greater dynamism despite being smaller in size than the pro-refugee community. Elite news media saw a decline in influence, highlighting the lack of intermediary sources between polarized users. While overall networked framing was positive about refugees during both crises, the framing of Ukrainian refugees was more complex and multifaceted. Our results underscore the disrupted state of public discourse on controversial topics and the need to reduce destructive polarization on social media.

Keywords

X, H, Refugee Crisis, Germany, Twitter, A, Social Sciences, Information technology, Mixed Methods, T58.5-58.64, Social Network Analysis, General Works

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Published in a Diamond OA journal