Media-based navigation for hypermedia systems
HYPERTEXT '93 Proceedings of the fifth ACM conference on Hypertext
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CHI 98 Cconference Summary on Human Factors in Computing Systems
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ECHT '94 Proceedings of the 1994 ACM European conference on Hypermedia technology
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CHI '01 Extended Abstracts on Human Factors in Computing Systems
Cheese: tracking mouse movement activity on websites, a tool for user modeling
CHI '01 Extended Abstracts on Human Factors in Computing Systems
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CHI '01 Extended Abstracts on Human Factors in Computing Systems
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SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction
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Proceedings of the 21st ACM conference on Hypertext and hypermedia
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Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Proceedings of the fifth ACM international conference on Web search and data mining
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Interactive hypervideo visualization for browsing behavior analysis
Proceedings of the 21st international conference companion on World Wide Web
User see, user point: gaze and cursor alignment in web search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Processing data on any sort of user interaction is well known to be cumbersome and mostly time consuming. In order to assist researchers in easily inspecting fine-grained browsing data, current tools usually display user interactions as mouse cursor tracks, a video-like visualization scheme. However, to date, traditional online video inspection has not explored the full capabilities of hypermedia and interactive techniques. In response to this need, we have developed SMT2ε, a Web-based tracking system for analyzing browsing behavior using feature-rich hypervideo visualizations. We compare our system to related work in academia and the industry, showing that ours features unprecedented visualization capabilities. We also show that SMT2ε efficiently captures browsing data and is perceived by users to be both helpful and usable. A series of prediction experiments illustrate that raw cursor data are accessible and can be easily handled, providing evidence that the data can be used to construct and verify research hypotheses. Considering its limitations, it is our hope that SMT2ε will assist researchers, usability practitioners, and other professionals interested in understanding how users browse the Web.