  Social behaviors involving the interaction of multiple individuals are
complex and frequently crucial for an animal's survival. These interactions,
ranging across sensory modalities, length scales, and time scales, are often
subtle and difficult to quantify. Contextual effects on the frequency of
behaviors become even more difficult to quantify when physical interaction
between animals interferes with conventional data analysis, e.g. due to visual
occlusion. We introduce a method for quantifying behavior in courting fruit
flies that combines high-throughput video acquisition and tracking of
individuals with recent unsupervised methods for capturing an animal's entire
behavioral repertoire. We find behavioral differences in paired and solitary
flies of both sexes, identifying specific behaviors that are affected by social
and spatial context. Our pipeline allows for a comprehensive description of the
interaction between multiple individuals using unsupervised machine learning
methods, and will be used to answer questions about the depth of complexity and
variance in fruit fly courtship.
