  In human and animal groups, social interactions often rely on the
transmission of information via visual observation of the behavior of others.
These visual interactions are governed by the laws of physics and sensory
limits. Individuals appear smaller when far away and thus become harder to
detect visually, while close by neighbors tend to occlude large areas of the
visual field and block out interactions with individuals behind them. Here, we
systematically study the effect of a group's spatial structure, its density as
well as polarization and aspect ratio of the physical bodies, on the properties
of the visual interaction network. In such a network individuals are connected
if they can see each other as opposed to other interaction models such as
metric or topological networks that omit these limitations due to the
individual's physical bodies. We study the effect that spatial configuration
has on the static properties of these networks as well as its influence on the
transmission of information or behaviors which we investigate via two generic
models of social contagion. We expect our work to have implications for the
study of animal groups, where it could inform the study of functional benefits
of different macroscopic states. It may also be applicable to the construction
of robotic swarms communicating via vision or for understanding the spread of
panics in human crowds.
