Altruistic Giving Toward Refugees: Identifying Factors That Increase Citizens' Willingness to Help

Over the past decade, the world has faced an unprecedented refugee crisis. The large number of incoming refugees represents a challenge for host societies and its citizens triggering reactions from a supportive welcome to brusque rejection and hostile behavior toward refugees. In a pre-registered study, we investigated factors that could promote altruistic behavior in fully incentivized one-shot Dictator Game toward various receiver groups including refugees. We find that host citizens behave more altruistically toward refugees and other receiver groups if they (a) share a local identity with them (i.e., live in the same city), and (b) perceive them to be close (to the self) and warm-hearted. Moreover, citizens that are (c) generally more prosocial and hold a more left-wing political orientation are more willing to give. Unexpectedly, from a theoretical point of view, altruistic giving toward refugees was not influenced in the predicted direction by a shared student identity, competition and perceived income differences (although the latter effect was significant when considering all receiver groups). For shared student identity we even observe a reduction of altruistic behavior, while the opposite effect was predicted. We discuss implications for public policies for successful refugee helping and integration.

Factors Predicting Willingness to Share COVID-19 Misinformation

We conducted a preregistered exploratory survey to assess whether patterns of individual differences in political orientation, social dominance orientation (SDO), traditionalism, conspiracy ideation, or attitudes about science predict willingness to share different kinds of misinformation regarding the COVID-19 pandemic online. Analyses revealed two orthogonal models of individual differences predicting the willingness to share misinformation over social media platforms. Both models suggest a sizable role of different aspects of political belief, particularly SDO, in predicting tendencies to share different kinds of misinformation, predominantly conspiracy theories. Although exploratory, results from this study can contribute to the formulation of a socio-cognitive profile of individuals who act as vectors for the spread of scientific misinformation online, and can be useful for computationally modeling misinformation diffusion.