- User studies in human-robot interaction and social robotics in general involve human participants and their reactions, observations and expectations of robots. This thesis presents two innovative experimental methods aimed at gaining access to high-stakes social data not typically collectable with traditional user studies. The Actor Method provides access to data that would not typically be approved by the experimental research board (privacy and data use in human-robot interaction) and the VR Method allows us to collect data about robot physical designs, without actually building all the robot variants. As a methods paper, this thesis presents the utilization of these two methods in two different HRI experiments and highlights the significance of this approach to both the experiments. Not only were both the methods successful at gaining access to the desired data, but they also helped elicit participants’ emotions and mental models about the robots and their interactions with the robots. Future work can extend the VR Method to create immersive extended reality story-like experiences that explore human-robot interactions with virtual robots and real-world haptics like water, wind and heat.