Data from: Detecting and quantifying social transmission using network-based diffusion analysis

We provide tutorials guiding users through several examples illustrating how to carry out network-based diffusion analysis using the NBDA package (https://github.com/whoppitt/NBDA). These tutorials make use of simulated data in the form of social networks and individual-level data (e.g. sex and age), which are provided here In addition, the NBDA code and data necessary to replicate the results presented in Box 3 in the main text are also included. These data were collected as part of a larger study examining the relative importance of different social network types in guiding honeybees to novel foraging locations. Two cohorts of honeybees originating from a single colony were simultaneously trained to separate artificial sugar water feeders 100 m from the hive. During the trial, one of these feeders was left empty, while the other continued to provide sucrose. The order in which individuals trained to the former feeder discovered the latter feeder (which they had never previously visited) was recorded. At the same time, all interactions in the hive between honeybees visiting the active feeder and those that had been trained to the now-empty feeder (but had yet to discover the active feeder) were filmed and recorded. For each dance-following interaction, the number of waggle runs an individual followed for the active feeder was recorded. For trophallaxis and antennation, the duration of each interaction was recorded in seconds. From these interaction records, dynamic and static social networks were constructed. Static networks for each interaction type aggregated all interactions that occurred between each pair across the entire 2 hr trial. In contrast, dynamic networks updated throughout the trial. For each successful recruitment event, networks updated when that individual left the hive. In one instance, a recruit left the hive, but did not discover the feeder until after another recruit had discovered it; to prevent networks from "rewinding", the update time for the latter individual was used for the former. There were 16 recruitment events in total, meaning networks were updated a total of 15 times. The index numbers indicate the successive updates.