Temporal dynamics of partisan identity fusion and prosociality during the 2016 U.S. Presidential Election

Abstract

We investigated the dynamics of identity fusion and prosocial behavior within political groups in the four weeks preceding and following the 2016 U.S. Presidential Election. The primary questions were whether a negative event (losing) would lead to a more pronounced increase in identity fusion, and whether identity fusion would predict prosocial giving. We found that while fusion gradually increased in the run-up to the election, there was no significant increase after the event for supporters of either party. We also found that identity fusion robustly predicted prosocial ingroup giving, especially before the election, and even when accounting for self-reported identification and previous political commitment behaviors. Implications for theories of identity fusion are discussed.

Keywords:

• Identity fusion
• prosociality
• dictator game
• presidential election

Notes

1. Another approach to investigating this question would be to fit a non-linear model, for example by including polynomial terms. However, with only 10 values for x (corresponding to our 10 time points), our ability to do so was limited. We opted for this interactive approach instead.

2. Some researchers have suggested that the Dictator Game should be modeled as censored data (Engel, 2011) on the rationale that the underlying preferences of some individuals would motivate them to take money away from their partner if that were possible (creating hypothetical negative values) or to give beyond their endowment if that were possible (creating hypothetical values above 40-cents). This implies that our data is left-censored at 0 and right-censored at 40 cents, and that a tobit model accounting for censoring would be appropriate. We re-ran our final models as left and right censored tobit models using the censReg package in R (Henningsen, 2017). This produced substantively identical conclusions though in the final model predicting giving via both fusion measures, time point, and party preferences, the 3-way interaction between the fusion measures and party preference was only marginally significant in the tobit model (p = .081, as compared to .027 in the linear model).