用Google Analytics分析健康网站用户寻找复杂健康信息的导航流程方法

IF 3.4 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Patrick Cheong-Iao Pang, Megan Munsie, Shanton Chang
{"title":"用Google Analytics分析健康网站用户寻找复杂健康信息的导航流程方法","authors":"Patrick Cheong-Iao Pang, Megan Munsie, Shanton Chang","doi":"10.3390/informatics10040080","DOIUrl":null,"url":null,"abstract":"People are increasingly seeking complex health information online. However, how they access this information and how influential it is on their health choices remains poorly understood. Google Analytics (GA) is a widely used web analytics tool and it has been used in academic research to study health information-seeking behaviors. Nevertheless, it is rarely used to study the navigation flows of health websites. To demonstrate the usefulness of GA data, we adopted both top-down and bottom-up approaches to study how web visitors navigate within a website delivering complex health information about stem cell research using GA’s device, traffic and path data. Custom Treemap and Sankey visualizations were used to illustrate the navigation flows extracted from these data in a more understandable manner. Our methodology reveals that different device and traffic types expose dissimilar search approaches. Through the visualizations, popular web pages and content categories frequently browsed together can be identified. Information on a website that is often overlooked but needed by many users can also be discovered. Our proposed method can identify content requiring improvements, enhance usability and guide a design for better addressing the needs of different audiences. This paper has implications for how web designers can use GA to help them determine users’ priorities and behaviors when navigating complex information. It highlights that even where there is complex health information, users may still want more direct and easy-to-understand navigations to retrieve such information.","PeriodicalId":37100,"journal":{"name":"Informatics","volume":"2 1","pages":"0"},"PeriodicalIF":3.4000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Method for Analyzing Navigation Flows of Health Website Users Seeking Complex Health Information with Google Analytics\",\"authors\":\"Patrick Cheong-Iao Pang, Megan Munsie, Shanton Chang\",\"doi\":\"10.3390/informatics10040080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"People are increasingly seeking complex health information online. However, how they access this information and how influential it is on their health choices remains poorly understood. Google Analytics (GA) is a widely used web analytics tool and it has been used in academic research to study health information-seeking behaviors. Nevertheless, it is rarely used to study the navigation flows of health websites. To demonstrate the usefulness of GA data, we adopted both top-down and bottom-up approaches to study how web visitors navigate within a website delivering complex health information about stem cell research using GA’s device, traffic and path data. Custom Treemap and Sankey visualizations were used to illustrate the navigation flows extracted from these data in a more understandable manner. Our methodology reveals that different device and traffic types expose dissimilar search approaches. Through the visualizations, popular web pages and content categories frequently browsed together can be identified. Information on a website that is often overlooked but needed by many users can also be discovered. Our proposed method can identify content requiring improvements, enhance usability and guide a design for better addressing the needs of different audiences. This paper has implications for how web designers can use GA to help them determine users’ priorities and behaviors when navigating complex information. It highlights that even where there is complex health information, users may still want more direct and easy-to-understand navigations to retrieve such information.\",\"PeriodicalId\":37100,\"journal\":{\"name\":\"Informatics\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/informatics10040080\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/informatics10040080","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

人们越来越多地在网上寻求复杂的健康信息。然而,他们如何获取这些信息,以及这些信息对他们的健康选择有多大影响,人们仍然知之甚少。谷歌分析(Google Analytics, GA)是一种广泛使用的网络分析工具,它已被用于研究健康信息寻求行为的学术研究。然而,它很少用于研究健康网站的导航流程。为了证明遗传算法数据的有用性,我们采用了自顶向下和自底向上的方法来研究网络访问者如何在使用遗传算法的设备、流量和路径数据提供有关干细胞研究的复杂健康信息的网站中导航。自定义树图和Sankey可视化被用来以一种更容易理解的方式说明从这些数据中提取的导航流。我们的方法表明,不同的设备和流量类型暴露了不同的搜索方法。通过可视化,可以识别出热门网页和经常一起浏览的内容类别。网站上经常被忽视但又被许多用户需要的信息也可以被发现。我们提出的方法可以识别需要改进的内容,增强可用性,并指导设计以更好地满足不同受众的需求。这篇论文暗示了网页设计师如何使用遗传算法来帮助他们确定用户在浏览复杂信息时的优先级和行为。它强调,即使存在复杂的健康信息,用户可能仍然需要更直接和易于理解的导航来检索这些信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method for Analyzing Navigation Flows of Health Website Users Seeking Complex Health Information with Google Analytics
People are increasingly seeking complex health information online. However, how they access this information and how influential it is on their health choices remains poorly understood. Google Analytics (GA) is a widely used web analytics tool and it has been used in academic research to study health information-seeking behaviors. Nevertheless, it is rarely used to study the navigation flows of health websites. To demonstrate the usefulness of GA data, we adopted both top-down and bottom-up approaches to study how web visitors navigate within a website delivering complex health information about stem cell research using GA’s device, traffic and path data. Custom Treemap and Sankey visualizations were used to illustrate the navigation flows extracted from these data in a more understandable manner. Our methodology reveals that different device and traffic types expose dissimilar search approaches. Through the visualizations, popular web pages and content categories frequently browsed together can be identified. Information on a website that is often overlooked but needed by many users can also be discovered. Our proposed method can identify content requiring improvements, enhance usability and guide a design for better addressing the needs of different audiences. This paper has implications for how web designers can use GA to help them determine users’ priorities and behaviors when navigating complex information. It highlights that even where there is complex health information, users may still want more direct and easy-to-understand navigations to retrieve such information.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Informatics
Informatics Social Sciences-Communication
CiteScore
6.60
自引率
6.50%
发文量
88
审稿时长
6 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信