From Perception to Trust: The Multidimensional Landscape of Anthropomorphism in Robotics
Xianru Shang, Zijian Liu, Chen Gong, Zhengyang He, Chengliang Wang
Abstract
The widespread application of robotic technology across social contexts has underscored the potential of anthropomorphic features in enhancing social attributes and user acceptance, drawing increasing academic attention. Despite its emergence as a prominent research topic in human-robot interaction (HRI), existing studies lack systematic bibliometric reviews. To address this gap, we conducted a comprehensive review of 1,082 academic publications from the Web of Science Core Collection. By constructing knowledge maps that include collaboration networks, co-citation clustering, and keyword co-occurrence analysis, we identified the developmental trajectory and key themes in anthropomorphism research within HRI. The analysis revealed three core components: application scenarios in HRI, anthropomorphism theory and psychological effects, social behavior and emotional interaction. Keyword clustering further identified four major research hotspots: system design, emotional interaction, user adoption and experience, and assistive interaction techniques. This study provides a comprehensive depiction of the knowledge landscape of anthropomorphic research in HRI, offering valuable references for further research direction.