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This lecture explores the growing issue of political polarization, focusing on its structural aspects from a network perspective. Delve into three key conceptualizations of polarization: issue/ideological polarization (diverging political views), affective polarization (increasing negative partisanship), and structural polarization (decreased interaction between groups). Learn how network-based structural analysis is particularly effective for studying polarization using big data from social media platforms, allowing examination of both ideological and affective dimensions. Examine findings from a longitudinal study of 11.5 million tweets across five topics (including immigration and climate change) on Finnish social media from 2015-2023. Discover how social media users can be categorized into ideological groups based on retweeting behavior, which groups drive polarization, how polarization evolves over time, and its underlying causes. The lecture concludes with methodological approaches for studying affective polarization through social media data using network analysis.
