Browsing by Subject "Mind perception"
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Item Open Access Explicit and implicit measurement of mind perception in social robots through individual differences modulation(Bilkent University, 2022-06) Saltık, İmgeThe attribution of mental states to the object or subject that an individual interacts with according to its appearance or behavior is called mind perception (Gray et al., 2007). Recent research on human-robot interaction has shown that robots can create mind perceptions like other agents under certain conditions. In addition, while the two dimensions of mind perception (Agency and Experience) are mostly controlled using explicit measurement methods in the literature, the use of implicit measurement methods in the measurement of mind perception is still almost nonexistent. In addition to this fundamental gap, studies examining mind perception in robots have investigated how appearance affects mind perception, while the effect of action perception almost again has never been observed. In this context, we investigated how robots affect mind perception by manipulating differences in action and appearance. Methodologically, we conducted our study using both the explicit measurement method and the implicit measurement method due to the gap in the literature. In this study, individual difference measurement was also used to observe the causes of different attributions in mind perception to robots. In the first study, participants (N=102) evaluated how the robots' performing different actions (biological, verbal and nonverbal communicative and neutral) and appearance (humanoid and mechanical) affect mind perception; in the second study, participants (N=185) evaluated the effect of robots' actions and appearances on mind perception in terms of implicit and explicit measurement methods. In addition, 11 individual difference measures were used to observe individual differences that modulate mind perception. Looking at the results, it has been observed in both studies that the action of robots affects mind perception. In the explicit measurement method, neutral behavior was found to create less mind perception than communicative and biological action. In the implicit measurement method, differences in reaction time were observed between communicative actions and biological \& neutral actions. Individual differences that modulate the perception of the explicit and implicit mind have been observed. According to this, intentionality of behavior, theory of mind, and perception of loneliness are core modulates for explicit mind perception, while negative mood primarily modulates implicit mind perception. Looking at the results, it was observed that the perception of action had an effect on the mind perception, the implicit and the explicit mind perception showed different patterns from each other, and the individual differences predicted the pattern of implicit and explicit mind perception.Item Open Access Studying mind perception in social robotics ımplicitly: the need for validation and norming(Association for Computing Machinery, 2023-03-13) Pekçetin, T. N.; Barinal, Badel; Tunç, J.; Acartürk, C.; Ürgen, Burcu AyşenThe recent shift towards incorporating implicit measurements into the mind perception studies in social robotics has come along with its promises and challenges. The implicit tasks can go beyond the limited scope of the explicit tasks and increase the robustness of empirical investigations in human-robot interaction (HRI). However, designing valid and reliable implicit tasks requires norming and validating all stimuli to ensure no confounding factors interfere with the experimental manipulations. We conducted a lexical norming study to systematically explore the concepts suitable for an implicit task that measures mind perception induced by social robots. Two-hundred seventy-four participants rated an expanded and strictly selected list of forty mental capacities in two categories: Agency and Experience, and in two levels of capacities: High and Low. We used the partitioning around medoids algorithm as an objective way of revealing the clusters. We discussed the different clustering solutions in light of the previous findings. We consulted on frequency-based natural language processing (NLP) on the answers to the open-ended questions. The NLP analyses verified the significance of clear instructions and the presence of some common conceptualizations across dimensions. We proposed a systematic approach that encourages validation and norming studies, which will further improve the reliability and reproducibility of HRI studies.