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Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis
User studies are typically difficult, recruiting enough users is often problematic and each experiment takes a considerable amount of time to be completed. In these studies, eye tracking is increasingly used which often increases time, therefore, the lower the number of users required for these stud...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bern Open Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141090/ https://www.ncbi.nlm.nih.gov/pubmed/33828666 http://dx.doi.org/10.16910/jemr.10.4.6 |
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author | Eraslan, Sukru Yesilada, Yeliz Harper, Simon |
author_facet | Eraslan, Sukru Yesilada, Yeliz Harper, Simon |
author_sort | Eraslan, Sukru |
collection | PubMed |
description | User studies are typically difficult, recruiting enough users is often problematic and each experiment takes a considerable amount of time to be completed. In these studies, eye tracking is increasingly used which often increases time, therefore, the lower the number of users required for these studies the better for making these kinds of studies more practical in terms of economics and time expended. The possibility of achieving almost the same results with fewer users has already been raised. Specifically, the possibility of achieving 75% similarity to the results of 65 users with 27 users for searching tasks and 34 users for browsing tasks has been observed in scanpath trend analysis which discovers the most commonly followed path on a particular web page in terms of its visual elements or areas of interest (AOIs). Different approaches are available to segment or divide web pages into their visual elements or AOIs. In this paper, we investigate whether the possibility raised by the previous work is restricted to a particular page segmentation approach by replicating the experiments with two other segmentation approaches. The results are consistent with ~5% difference for the searching tasks and ~10% difference for the browsing tasks. |
format | Online Article Text |
id | pubmed-7141090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Bern Open Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-71410902021-04-06 Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis Eraslan, Sukru Yesilada, Yeliz Harper, Simon J Eye Mov Res Research Article User studies are typically difficult, recruiting enough users is often problematic and each experiment takes a considerable amount of time to be completed. In these studies, eye tracking is increasingly used which often increases time, therefore, the lower the number of users required for these studies the better for making these kinds of studies more practical in terms of economics and time expended. The possibility of achieving almost the same results with fewer users has already been raised. Specifically, the possibility of achieving 75% similarity to the results of 65 users with 27 users for searching tasks and 34 users for browsing tasks has been observed in scanpath trend analysis which discovers the most commonly followed path on a particular web page in terms of its visual elements or areas of interest (AOIs). Different approaches are available to segment or divide web pages into their visual elements or AOIs. In this paper, we investigate whether the possibility raised by the previous work is restricted to a particular page segmentation approach by replicating the experiments with two other segmentation approaches. The results are consistent with ~5% difference for the searching tasks and ~10% difference for the browsing tasks. Bern Open Publishing 2017-11-22 /pmc/articles/PMC7141090/ /pubmed/33828666 http://dx.doi.org/10.16910/jemr.10.4.6 Text en This work is licensed under a Creative Commons Attribution 4.0 International License, ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Article Eraslan, Sukru Yesilada, Yeliz Harper, Simon Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis |
title | Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis |
title_full | Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis |
title_fullStr | Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis |
title_full_unstemmed | Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis |
title_short | Less Users More Confidence: How AOIs Don't Affect Scanpath Trend Analysis |
title_sort | less users more confidence: how aois don't affect scanpath trend analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141090/ https://www.ncbi.nlm.nih.gov/pubmed/33828666 http://dx.doi.org/10.16910/jemr.10.4.6 |
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