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An eye‐tracking approach to the analysis of relevance judgments on the Web: The case of Google search engine

Balatsoukas, Panos ; Ruthven, Ian

Journal of the American Society for Information Science and Technology, September 2012, Vol.63(9), pp.1728-1746 [Tạp chí có phản biện]

ISSN: 1532-2882 ; E-ISSN: 1532-2890 ; DOI: 10.1002/asi.22707

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  • Nhan đề:
    An eye‐tracking approach to the analysis of relevance judgments on the Web: The case of Google search engine
  • Tác giả: Balatsoukas, Panos ; Ruthven, Ian
  • Chủ đề: Judgment ; User Studies ; Information Seeking
  • Là 1 phần của: Journal of the American Society for Information Science and Technology, September 2012, Vol.63(9), pp.1728-1746
  • Mô tả: Eye movement data can provide an in‐depth view of human reasoning and the decision‐making process, and modern information retrieval () research can benefit from the analysis of this type of data. The aim of this research was to examine the relationship between relevance criteria use and visual behavior in the context of predictive relevance judgments. To address this objective, a multimethod research design was employed that involved observation of participants’ eye movements, talk‐aloud protocols, and postsearch interviews. Specifically, the results reported in this article came from the analysis of 281 predictive relevance judgments made by 24 participants using the oogle search engine. We present a novel stepwise methodological framework for the analysis of relevance judgments and eye movements on the Web and show new patterns of relevance criteria use during predictive relevance judgment. For example, the findings showed an effect of ranking order and surrogate components (itle, ummary, and ) on the use of relevance criteria. Also, differences were observed in the cognitive effort spent between very relevant and not relevant judgments. We conclude with the implications of this study for research.
  • Số nhận dạng: ISSN: 1532-2882 ; E-ISSN: 1532-2890 ; DOI: 10.1002/asi.22707

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