Social networks predict selective observation and information spread in ravens

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation, and learning patterns, we investigated information transmission in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions, and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behavior was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner and being observed frequently. Network-Based Diffusion Analysis (NBDA) revealed that the order in which ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens from three families. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission

Sharing of science is most likely among male scientists

Abstract Humans are considered to be highly prosocial, especially in comparison to other species. However, most tests of prosociality are conducted in highly artificial settings among anonymous participants. To gain a better understanding of how human hyper-cooperation may have evolved, we tested humans’ willingness to share in one of the most competitive fields of our current society: academia. Researchers were generally prosocial with 80% sharing a PDF of one of their latest papers, and almost 60% willing to send us their data. Intriguingly, prosociality was most prominent from male to male, and less likely among all other sex-combinations. This pattern suggests the presence of male-exclusive networks in science, and may be based on an evolutionary history promoting strong male bonds