Human swarm interaction (HSI) involves gathering information about a swarm’s state as it evolves and using it to make informed decisions on how to influence the collective behavior of the swarm. In order to determine the proper input, an operator must have an accurate representation and understanding of the current swarm state, including what emergent behavior is currently happening, as well as what impact the behavior will have on the swarm's future state. The studies herein investigate how recognition differs between different behaviors, and how different methods of displaying the swarm state impact the ability of operators to predict future states. The results show that both the behavior and visualization of the swarm impact recognition and predictability---specifically, that operators view swarm's as a single entity, rather than a collection of different agents. Therefore, we suggest that designers of HSI systems display the swarm to the operator in a manner that supports a holistic view of the swarm.