How do users grow up along with search engines?: a study of long-term users' behavior

  • Authors:

  • Jian Liu;Yiqun Liu;Min Zhang;Shaoping Ma

  • Affiliations:

  • State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China;State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China

  • Venue:
  • Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
  • Year:
  • 2013

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Abstract

With a stronger reliance on search engines in our daily life, a large number of studies have investigated user behavior characteristics in Web search. However, previous studies mainly focus on large-scale query log data and analyze temporal changes based on all users without differentiating different user groups; few have really traced a fixed and long-term group of users and have distinguished the behavior of long-term users from ordinary users to analyze long-term temporal changes unbiasedly. In this paper we look into the interaction logs of these two user groups to analyze differences between these two user groups and to better understand how users grow up along with Web search engines. Statistical and experimental results show that there exist temporal changes of both user groups. There are also significant differences between these two user groups in the frequency of interaction, complexity of search tasks, and query formulation conventions. The findings have implications for how Web search engines should better support users' information seeking process by tackling complex search tasks and complicated query formulations.