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The Effects of Search Task Determinability on Search Behavior

Part of the Lecture Notes in Computer Science book series (LNISA,volume 10193)

Abstract

Among the many task characteristics that influence search behaviors and outcomes, task complexity has received considerable attention. One view of task complexity is through the lens of a priori determinability—a measure of how much the searcher knows about the task outcomes, information requirements, and processes involved. In this paper, we explore a novel manipulation of a priori determinability in the context of comparative search tasks, which require comparing items (or alternatives) along different dimensions. Our manipulation involved explicitly including the items to be compared and/or the dimension by which to compare items in the search task description. We report on two user studies that investigate the effects of our manipulation on searchers’ pre-task perceptions, search behaviors and post-task outcomes. Our results found that specifying the items had an effect on searchers’ pre-task perceptions, but not their search behaviors and outcomes, and that specifying the dimension had no effect on perceptions, but made the task more difficult by possibly introducing uncertainty into the search process.

Keywords

  • Search Task
  • Search Effort
  • Search Behavior
  • Comparative Task
  • Task Characteristic

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Fig. 1.

Notes

  1. 1.

    Task descriptions are available at https://ils.unc.edu/searchstructures/resources/ecir2017_tasks.txt.

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Acknowledgments

This work was supported in part by NSF grants IIS-1552587 and IIS-1451668. Any opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF.

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Correspondence to Rob Capra .

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Capra, R., Arguello, J., Zhang, Y. (2017). The Effects of Search Task Determinability on Search Behavior. In: , et al. Advances in Information Retrieval. ECIR 2017. Lecture Notes in Computer Science(), vol 10193. Springer, Cham. https://doi.org/10.1007/978-3-319-56608-5_9

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  • DOI: https://doi.org/10.1007/978-3-319-56608-5_9

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