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How Self-Sentiments And Personal Networks Impact Political Polarization, Matthew Facciani

Theses and Dissertations

This project investigates how identities, self-sentiments, and personal network composition impact political polarization. I apply the framework of Affect Control Theory to capture how Democrats and Republicans feel about their political ingroup and outgroups (through evaluation, potency and activity ratings) and evaluate the likelihood of events involving these groups. In my first experiment, I study if self-uncertainty and self-affirmation primes impact political bias. I also apply Affect Control Theory-Self to measure self-sentiment change (self-evaluation, self-potency, and self-activity) from these primes as well. I predict that priming self-uncertainty should increase political bias (due to inflated self-sentiments) and that priming self-affirmation should …