Multi-organizational cross-sector partnerships on social media involving nonprofits, governments, and corporations are increasingly important for addressing complex social issues. Such large-scale cross-sector networks would not be possible without brokers who connect otherwise disconnected clusters. Nevertheless, cross-sector brokers are not always positively received by the public. Drawing from the brokerage typology literature, we classify five distinctive types of brokers (i.e., representative, gatekeeper, liaison, itinerant, and coordinator) and explore public responses associated with them, and how such effects spill over to connected same-sector organizations. Our findings show that different types of brokers receive different public responses, which are moderated by organizations’ sectors. In particular, nonprofits playing brokerage roles are more likely to be positively received by the public compared to government agencies.

In this paper, we seek to advance an updated concept of social space that integrates the multilayer and dynamic statistical network methods currently at the disposal of social network researchers. We demonstrate the analytic value of the new concept of social space that we propose with the help of an illustrative analysis of an organizational field involving organizations' external and internal decisions that congeal into a multilevel system of action that shapes the space of possibilities for other participants in the field. Through these internal and external decisions, organizations seek certain positions in their social space while simultaneously modifying that social space over time. We conclude by arguing that network researchers' choices of goodness-of-fit statistics should reflect a consideration about the dimensions of social space of most interest to the nodes involved.