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Factors influencing viewing behaviour on search engine results pages: a review of eye-tracking research
Behaviour & Information Technology ( IF 2.9 ) Pub Date : 2020-05-22 , DOI: 10.1080/0144929x.2020.1761450
Dirk Lewandowski 1 , Yvonne Kammerer 2, 3
Affiliation  

ABSTRACT

Eye-tracking research is beneficial for better understanding user behaviour in search engines. The present paper presents a comprehensive narrative literature review of eye-tracking studies examining factors influencing users’ viewing behaviour on results pages of search engines. Discipline-specific databases from Psychology, Computer Science, and Library and Information Science, as well as one multidisciplinary database have been searched for relevant articles. Criteria for inclusion were that a paper reported empirical results from an eye-tracking study in which effects of a specific factor on users’ viewing behaviour on search engine results pages (SERPs) were examined, with inferential statistical results being reported. This led to a set of 41 papers that were further examined. The papers were grouped into three categories according to three types of factors that may affect individuals’ web search activities: contextual factors, resource factors, and individual factors. Papers were assigned to these categories and subsequently to sub-categories. Overall, while for some sub-categories robust findings can be reported, we found results in many sub-categories to be inconclusive. For future research, we recommend a shift from small-scale studies examining single factors to more comprehensive and theory-driven research using larger sample sizes.



中文翻译:

影响搜索引擎结果页面浏览行为的因素:眼动追踪研究综述

摘要

眼球追踪研究有助于更好地了解搜索引擎中的用户行为。本论文对眼球追踪研究进行了全面的叙述性文献综述,研究了影响用户在搜索引擎结果页面上查看行为的因素。已经搜索了心理学、计算机科学、图书馆和信息科学的特定学科数据库以及一个多学科数据库中的相关文章。纳入标准是一篇论文报告了一项眼动追踪研究的实证结果,其中检查了特定因素对用户在搜索引擎结果页面 (SERP) 上的查看行为的影响,并报告了推论统计结果。这导致了一组 41 篇论文被进一步审查。根据可能影响个人网络搜索活动的三类因素,将论文分为三类:上下文因素、资源因素和个人因素。论文被分配到这些类别,随后被分配到子类别。总体而言,虽然对于某些子类别可以报告可靠的发现,但我们发现许多子类别的结果尚无定论。对于未来的研究,我们建议从小规模研究转变为使用更大样本量的更全面和理论驱动的研究。我们发现许多子类别的结果是不确定的。对于未来的研究,我们建议从小规模研究转变为使用更大样本量的更全面和理论驱动的研究。我们发现许多子类别的结果是不确定的。对于未来的研究,我们建议从小规模研究转变为使用更大样本量的更全面和理论驱动的研究。

更新日期:2020-05-22
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