The fitness of group-living animals often depends on the efficiency with which members share information about resources, so that the group can collectively decide how best to allocate its efforts.Theoretical studies have shown that collective choices can emerge from homogeneous individuals following identical rules, but real animals show much evidence for heterogeneity in the degree and nature of their contribution to group decisions. In the social insects, for example, the transmission and processing of information is influenced by an often-neglected but well-organized division of labor of behaviorally heterogeneous workers. Studies that accurately quantify how this behavioral heterogeneity affects the spread of information among group members are still lacking. In this paper, we look at nest choices during colony emigrations of the ant Temnothorax rugatulus and measure the degree of behavioral heterogeneity of workers. Using both machine learning and network science methods, we identify and characterize behavioral categories of workers, and we analyze workers' contributions to the spread of information during each emigration.foraging patches (Detrain and Deneubourg 2008;Pablo et al. 2010), or suddenly changing the direction of group motion (Couzin et al. 2005; Conradt and Roper 2010) are just a few among many examples of collective decisions. Despite the diversity in behavioral mechanisms that have evolved to address these and similar problems, the underlying strategies for gathering, sharing, and processing the information necessary to address the problem at hand share many commonalities across species. Collectives pool information to mitigate the effect of uncertainty and increase decision accuracy (Conradt 2012), which requires efficient spread of information from informed individuals to uninformed ones (Ward et al. 2008;Franks et al. 2002;Couzin et al. 2005).