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User Assessment of Webpage Usefulness

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Human-Computer Interaction. Design and User Experience Case Studies (HCII 2021)

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Abstract

During a web search, the search engines provide relevant pages while the users decide the usefulness of them. The usefulness assessment has been found to be related to various factors. In this study, the effects of task domain and task type on webpage usefulness assessment were investigated. The two task domains involved were health and travel and the two task types were fact finding and decision making. In an experimental environment, 24 participants were asked to do internet search on 4 pre-defined tasks. In the interview after each search task, the users were asked to evaluate the usefulness of each web page they had clicked and talked about why the page was evaluated as such. According to the results of the experiment, we found that the task domain, task type, and various other factors had impacts on the usefulness assessment during web search.

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References

  1. Barry, C.L.: User-defined relevance criteria: an exploratory study. J. Am. Soc. Inform. Sci. 45(3), 149–159 (1994). https://doi.org/10.1002/(SICI)1097-4571(199404)45:3%3c149:AID-ASI5%3e3.0.CO;2-J

    Article  Google Scholar 

  2. Borlund, P.: The IIR evaluation model: a framework for evaluation of interactive information retrieval systems. Inform. Res. 8(3), 152 (2003). http://informationr.net/ir/8-3/paper152.html

  3. Chu, H.: Factors affecting relevance judgment: a report from TREC Legal track. J. Documentation 67(2), 264–278 (2011). https://doi.org/10.1108/00220411111109467

    Article  Google Scholar 

  4. Crystal, A., Greenberg, J.: Relevance criteria identified by health information users during web searches. J. Am. Soc. Inform. Sci. Technol. 57(10), 1368–1382 (2006). https://doi.org/10.1002/asi.20436

    Article  Google Scholar 

  5. Freund, L.: A cross-domain analysis of task and genre effects on perceptions of usefulness. Inf. Process. Manage. 49(5), 1108–1121 (2013). https://doi.org/10.1016/j.ipm.2012.08.007

    Article  Google Scholar 

  6. Freund, L., Berzowska, J.: The goldilocks effect: task-centred assessments of e-government information. Proc. Am. Soc. Inform. Sci. Technol. 47(1), 1–10 (2010). https://doi.org/10.1002/meet.14504701261

    Article  Google Scholar 

  7. Kinley, K., Tjondronegoro, D., Partridge, H., Edwards, S.: Relationship between the nature of the search task types and query reformulation behaviour. In: Proceedings of the Seventeenth Australasian Document Computing Symposium, pp. 39–46. ACM, New York, NY, USA (2012). https://doi.org/10.1145/2407085.2407091

  8. Kim, J.: Task as a context of information seeking: an investigation of daily life tasks on the web. Libri, vol. 58, no. 3 (2008). https://doi.org/10.1515/libr.2008.018

  9. Radlinski, F., Kurup, M., Joachims, T.: How does clickthrough data reflect retrieval quality? In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp. 43–52. ACM, New York, NY, USA (2008). https://doi.org/10.1145/1458082.1458092

  10. Ruthven, I., Baillie, M., Elsweiler, D.: The relative effects of knowledge, interest and confidence in assessing relevance. J. Documentation 63(4), 482–504 (2007). https://doi.org/10.1108/00220410710758986

    Article  Google Scholar 

  11. Saracevic, T.: The stratified model of information retrieval interaction: extension and applications. Proc. ASIS Ann. Meet. 34, 313–27 (1997)

    Google Scholar 

  12. Scholer, F., Kelly, D., Wu, W.-C., Lee, H.S., Webber, W.: The effect of threshold priming and need for cognition on relevance calibration and assessment. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 623–632 (2013)

    Google Scholar 

  13. Taylor, A.: User relevance criteria choices and the information search process. Inf. Process. Manage. 48(1), 136–153 (2012). https://doi.org/10.1016/j.ipm.2011.04.005

    Article  Google Scholar 

  14. Tombros, A., Ruthven, I., Jose, J.M.: How users assess web pages for information seeking. J. Am. Soc. Inform. Sci. Technol. 56(4), 327–344 (2005). https://doi.org/10.1002/asi.20106

    Article  Google Scholar 

  15. Toms, E.G., Freund, L., Kopak, R., Bartlett, J.C.: The effect of task domain on search. In: Proceedings of the 2003 Conference of the Centre for Advanced Studies on Collaborative Research, pp. 303–312. IBM Press, Toronto, Ontario, Canada (2003). http://dl.acm.org/citation.cfm?id=961322.961370

  16. Xie, I., Benoit III, E., Zhang, H.: How do users evaluate individual documents? an analysis of dimensions of evaluation activities. Inform. Res. 15(4), 723 (2010). http://InformationR.net/ir/15-4/colis723.html]

  17. Xu, Y., Chen, Z.: Relevance judgment: what do information users consider beyond topicality? J. Am. Soc. Inform. Sci. Technol. 57(7), 961–973 (2006). https://doi.org/10.1002/asi.20361

    Article  Google Scholar 

  18. Sillence, E., Briggs, P., Fishwick, L., Harris, P.: Trust and mistrust of online health sites. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 663–670 (2004)

    Google Scholar 

  19. Liao, Q.V., Fu, W.T.: Age differences in credibility judgments of online health information. ACM Trans. Comput.-Hum. Interact. 21(1), 1–23 (2014)

    Article  Google Scholar 

  20. Kourouthanassis, P.E., Mikalef, P., Pappas, I.O., Kostagiolas, P.: Explaining travellers online information satisfaction: a complexity theory approach on information needs, barriers, sources and personal characteristics. Inf. Manag. 54(6), 814–824 (2017)

    Article  Google Scholar 

  21. Toms, E.G., et al.: Task effects on interactive search: the query factor. In: Fuhr, N., Kamps, J., Lalmas, M., Trotman, A. (eds.) INEX 2007. LNCS, vol. 4862, pp. 359–372. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-85902-4_31

    Chapter  Google Scholar 

  22. Agichtein, E., Zheng, Z.: Identifying “best bet” web search results by mining past user behavior. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 902–908. ACM, New York, NY, USA (2006). https://doi.org/10.1145/1150402.1150526

  23. Vakkari, P., Hakala, N.: Changes in relevance criteria and problem stages in task performance. J. Documentation 56(5), 540–562 (2000)

    Google Scholar 

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Acknowledgements

This experiment was supported by the research grant awarded by the university’s Graduate Student Association. We also thank all the participants.

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Sa, N., Yuan, X. (2021). User Assessment of Webpage Usefulness. In: Kurosu, M. (eds) Human-Computer Interaction. Design and User Experience Case Studies. HCII 2021. Lecture Notes in Computer Science(), vol 12764. Springer, Cham. https://doi.org/10.1007/978-3-030-78468-3_30

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  • DOI: https://doi.org/10.1007/978-3-030-78468-3_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78467-6

  • Online ISBN: 978-3-030-78468-3

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