Sammendrag
This article investigates different polarizing mechanisms—relational homophily and
ideological partisanship—characterizing political communications using Twitter data
collected during the 2017 Norwegian election. By combining two computational
approches—partition-specific network analysis and quantitative analysis of language
polarization—we can examine the linkages between the structure of interactions and
political polarization. The results show that the Norwegian political Twittersphere is not
made of isolated echo chambers but is structured around crosscutting communities of
interaction. There are no signs that communities with higher degrees of polarization are
the ones that display higher degrees of homophily. Yet, the degree of ideological
polarization differs across communities and topics. Some topics, such as political hate and
far right and economy and taxes, are more polarized than others.
Vis fullstendig beskrivelse