Large scale analysis of web revisitation patterns

  • Authors:
  • Eytan Adar;Jaime Teevan;Susan T. Dumais

  • Affiliations:
  • University of Washington, Seattle, WA, USA;Microsoft Research, Redmond, WA, USA;Microsoft Research, Redmond, WA, USA

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2008

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Abstract

Our work examines Web revisitation patterns. Everybody revisits Web pages, but their reasons for doing so can differ depending on the particular Web page, their topic of interest, and their intent. To characterize how people revisit Web content, we analyzed five weeks of Web interaction logs of over 612,000 users. We supplemented these findings by a survey intended to identify the intent behind the observed revisitation. Our analysis reveals four primary revisitation patterns, each with unique behavioral, content, and structural characteristics. Through our analysis we illustrate how understanding revisitation patterns can enable Web sites to provide improved navigation, Web browsers to predict users' destinations, and search engines to better support fast, fresh, and effective finding and re-finding.