Why partisans feel hated: Distinct static and dynamic relationships with animosity meta-perceptions.

Area of Science:

• Political Science
• Social Psychology
• Communication Studies

Background:

• Partisan animosity and inaccurate perceptions of opposing political groups are prevalent.
• Understanding the drivers of these inaccurate perceptions, particularly partisan animosity meta-perceptions, is crucial for democratic discourse.

Purpose of the Study:

• To investigate the static and dynamic relationships between predictors and partisan animosity meta-perceptions.
• To examine how social media political posting relates to individuals' beliefs about how much opposing partisans dislike them.

Main Methods:

• Utilized panel data from the 2020 US presidential election.
• Analyzed both cross-sectional (static) and longitudinal (dynamic) relationships between variables and meta-perceptions.
• Focused on social media political posting as a key predictor.

Main Results:

• Social media posting showed no static relationship with meta-perceptions across different individuals.
• Within individuals, increased political posting over time (dynamic) was associated with more accurate meta-perceptions.
• Findings highlight distinct static and dynamic effects, challenging generalized conclusions.

Conclusions:

• Oversimplified claims about predictors of partisan animosity meta-perceptions, including social media activity, are often inaccurate.
• The relationship between meta-perceptions and other factors is context-dependent and can change over time.
• Dynamic analysis is essential for understanding how individual behaviors influence political perceptions.