Associating search and navigation behavior through log analysis

Mazlita Mat‐Hassan and Mark Levene

Journal of the American Society for Information Science and Technology, 2005, vol. 56, issue 9, 913-934

Abstract: We report on a study that was undertaken to better understand search and navigation behavior by exploiting the close association between the process underlying users' query submission and the navigational trails emanating from query clickthroughs. To our knowledge, there has been little research towards bridging the gap between these two important processes pertaining to users' online information searching activity. Based on log data obtained from a search and navigation documentation system called AutoDoc, we propose a model of user search sessions and provide analysis on users' link or clickthrough selection behavior, reformulation activities, and search strategy patterns. We also conducted a simple user study to gauge users' perceptions of their information seeking activity when interacting with the system. The results obtained show that analyzing both the query submissions and navigation starting from query clickthrough, reveals much more interesting patterns than analyzing these two processes independently. On average, AutoDoc users submitted only one query per search session and entered approximately two query terms. Specifically, our results show how AutoDoc users are more inclined to submit new queries or resubmit modified queries than to navigate by link‐following. We also show that users' behavior within this search system can be approximated by Zipf's Law distribution.

Date: 2005
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