Understanding the link between individual behavior and population-level phenomena has long been central in ecology and evolutionary biology. Behavior is a response to intrinsic and extrinsic factors including individual state, ecological factors or social interactions. Within a group each individual can be seen as part of a network of social interactions varying in strength, type and dynamic. The structure of this network can deeply impact the ecology and evolution of individuals, populations and species. Within a group social transmission of behavior can take many forms and may deeply affect individual’s behavior. Social learning has been studied mostly in fish, birds and mammals including humans. In insects, social learning has been unambiguously demonstrated in social Hymenoptera but this probably reflects limited research effort and recent evidence show that even non-eusocial insects such as Drosophila can copy the behavior of others. Compared to individual learning, which requires a trial and error period in every generation, social learning can potentially result in stable tradition transmission across generations. Despite the potential importance of social transmission on animal behavior relatively little is known about the processes which may facilitates or prevent this transmission and the relationship between social network structure and efficiency of social transmission. The goal of this project is to study the genetic and socio-environmental factors affecting social transmission with the integration of experimental approach, social network analysis and modeling. More specifically DrosoNet focuses on the mechanisms of information transfers that generate social learning. The originality of the program is to integrate complementary approaches (behavioral and social) devoted traditionally to very distinct biological models characterized by strongly divergent group organizations. This approach can help us identify patterns of social interaction (including how they change with time) that can lay the foundation for understanding key components of social transmission, and for making comparison of different populations, context or species, in order to understand at a global scale the emergence of cultures. Using Drosophila as an experimental model system and social network analysis the project will investigate (1) how the structure of a group affects social transmission (2) how individuals treat different source of information (in particular personal vs. social information) (3) the genetic bases of social learning ability. Importantly we aim at combining different approaches in order to understand whether a relationship between social network structures and dynamic can reflect the efficiency of social transmission i.e. can we use social network analysis in order to predict social transmission of information and ultimately the evolutionary trajectory of a group?