The recent literature of social preferences for inequality and redistribution has highlighted a concrete challenge: shifting attitudes towards redistributive policies is inherently hard. Survey experiments with informational and emotional treatments proved effective to improve knowledge and remove biases about specific issues, and, moreover, to increase concern for inequality in general. However, they largely failed to increase preferences for specific socio-economic policies aiming at reducing inequality, especially those involving governmental interventions. Often, the effect is much reduced, or even reversed, for republican respondents, who might even become more polarized on the issue. Two further limitations on the literature on social preferences for redistribution are found: (i) little is known about the effect of informational and emotional treatments on behavior (rather than just preference),
and (ii) there is an almost complete neglect for network effects. In fact, social networks are the foci of human political decision making and the preferential tool to achieve behavioral change—or opinion change with a stake—via complex contagion processes. Therefore, networks appear as the natural settings for an experiment aiming at shifting preferences for socio-economic outcomes. In this study, we address the question “Can we study preferences for redistributive policies in network settings and make a targeted network intervention to shift these for left-wing and right-wing individuals alike?” We designed a network-based online experiments using the nodeGame platform; the experiment is currently being implemented and we expect to perform the whole data collection in March 2019 and to present the first results at the IMEBESS conference 2019.