Affective polarization and dynamics of information spread in online networks

This paper investigates affective polarization in online networks, focusing on how emotions, network structure, partisanship, and information spread interact. The study analyzes discussions on Twitter about abortion and the COVID-19 pandemic, finding that users express more negative emotions toward those with opposing viewpoints. Affective polarization extends beyond simple in-group/out-group dynamics, with negative emotions increasing with network distance. Information spread also varies across groups, influenced by emotional salience to ideological divisions. The research provides insights into the emotional foundations of political discourse on social media and the interplay between emotions and network structure.

Kristina Lerman, Dan Feldman, Zihao He, Ashwin Rao