Date of Award
Open Access Dissertation
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 decrease political bias (due to inflating self-sentiments). My results show that there is strong political bias in both Democrats and Republicans with each group rating their outgroup lower on EPA. When analyzing if psychological primes could influence this baseline bias, I find that self-uncertainty increased negative evaluations towards one’s political outgroup. Finally, I found that I could detect self-sentiment change on the self-evaluation dimension from these psychological primes. Thus, Affect Control Theory could capture political polarization, self-sentiment change from psychological primes, and these primes did have an impact on political bias.
My second study analyzed how personal network composition influenced political bias. I predicted that increased political homogeneity in one’s personal network would be associated with greater political bias (measured through feelings towards one’s outgroup, subjective likelihood of events involving political groups, and strength of political ideology). Increased homogeneity was associated with decreased evaluation and potency of the outgroup as well as biased information processing for evaluating the likelihood of events involving the political groups. Additionally, greater homogeneity was associated with increased strength in political ideology, but only in Republicans. Finally, I found that evaluating one’s outgroup less negatively was associated with higher agreement with political beliefs associated with one’s outgroup. The results of this project demonstrate that self-sentiments and personal networks can influence political bias.
Facciani, M.(2020). How Self-Sentiments and Personal Networks Impact Political Polarization. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/6035