Combining Ethnographic and Clickstream Data to Identify User Web Browsing Strategies

Lillian Clark, I-Hsien Ting, Chris Kimble (), P. C. Wright and Daniel Kudenko
Additional contact information
Lillian Clark: HRMM - Portsmouth Business School
I-Hsien Ting: Department of Information Management - National Kaohsiung University of Applied Sciences
P. C. Wright: CS-YORK - Department of Computer Science [York] - University of York [York, UK]
Daniel Kudenko: CS-YORK - Department of Computer Science [York] - University of York [York, UK]

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Abstract: Introduction: The strategies that people use to browse Websites are difficult to analyse and understand: quantitative data can lack information about what a user actually intends to do, while qualitative data tends to be localised and is impractical to gather for large samples. Method: This paper describes a novel approach that combines data from direct observation, user surveys and server logs to analyse users' browsing behaviour. It is based on a longitudinal study of university students' use of a Website related to one of their courses. Analysis: The data were analysed by using Footstep graphs to categorise browsing behaviour into pre-defined strategies and comparing these with data from questionnaires and direct observation of the students' actual use of the site. Results: Initial results indicated that in certain cases the patterns from server logs matched the observed browsing strategies as described in the literature. In addition, by cross-referencing the quantitative and qualitative data, a number of insights were gained into potential problems. Conclusion: This study shows how combining quantitative and qualitative approaches can provide an insight into changes in user browsing behaviour over time. It also identifies some potential methodological problems in studies of browsing behaviour and indicates some directions for future research.

Keywords: Human-Computer interaction; User studies; Web usage mining; Information seeking behaviour; user behaviour (search for similar items in EconPapers)
Date: 2006-01-02
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00489627v1
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Published in Information Research: an international electronic journal, 2006, 11 (2), paper 249

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