Abstract
With the development of machine learning, high-level automation in many aspects is promising or even fledgling. However, a challenge that appears at this moment is that how people trust in automation. This study is a systematic literature review of this topic using bibliometric analysis. Tools like Scopus, VOSviewer, AuthorMapper, MAXQDA, Vicinitas, Harzing's Publish or Perish, and Web of Science are used to conduct bibliometric analyses and content analyses. The results identify the most influential publications and trends of research topics. In addition, topics related to automated vehicles are found to be high-profile applications in the area.
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Zhang, Z., Duffy, V.G., Tian, R. (2021). Trust and Automation: A Systematic Review and Bibliometric Analysis. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Design and User Experience. HCII 2021. Lecture Notes in Computer Science(), vol 13094. Springer, Cham. https://doi.org/10.1007/978-3-030-90238-4_32
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