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Bibliometric and Visualized Analysis of User Experience Design Research: From 1999 to 2019

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  • Rui Li
  • Hong Zhang
  • Chenguang Liu
  • Zhenyu Cheryl Qian
  • Linghao Zhang

Abstract

With increasing research attention to user experience (UX), UX design (UXD) has gained concomitant interest. This study systematically reviews UXD research using a bibliometrical knowledge map. We collected and reviewed 14,825 documents to analyze UXD research from five perspectives: keyword trends, reference co-citation, author co-citation, categories, and author institutes. (a) UXD, as a research term, broadens the boundaries of experience and design and brings them together. (b) Publications in UXD focus on user, business, and technology orientation. (c) Author co-citation analysis reveals “invisible college networks†among UXD scholars. (d) Computer Science and Engineering are the most significant majors in UXD, although interdisciplinary research is common. (e) Research from the United States dominates. This review recognizes research gaps and future trends for conceptualizing and assessing UXD skills. The findings can benefit researchers, curriculum designers, and instructors.

Suggested Citation

  • Rui Li & Hong Zhang & Chenguang Liu & Zhenyu Cheryl Qian & Linghao Zhang, 2022. "Bibliometric and Visualized Analysis of User Experience Design Research: From 1999 to 2019," SAGE Open, , vol. 12(1), pages 21582440221, March.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:1:p:21582440221087266
    DOI: 10.1177/21582440221087266
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    1. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Baldwin, Carliss & Hienerth, Christoph & von Hippel, Eric, 2006. "How user innovations become commercial products: A theoretical investigation and case study," Research Policy, Elsevier, vol. 35(9), pages 1291-1313, November.
    3. Park, Eunil, 2019. "Motivations for customer revisit behavior in online review comments: Analyzing the role of user experience using big data approaches," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 14-18.
    4. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    5. Henry Small, 1973. "Co‐citation in the scientific literature: A new measure of the relationship between two documents," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 24(4), pages 265-269, July.
    6. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
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