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

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

Content Provider	ACM Digital Library
Author	Zhang, Min Ma, Shaoping Liu, Jian Liu, Yiqun
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.
Starting Page	1795
Ending Page	1800
Page Count	6
File Format	PDF
ISBN	9781450322638
DOI	10.1145/2505515.2505650
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-10-27
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Interactive degree Web search engine Query formulation conventions User behavior analysis Search task complexity
Content Type	Text
Resource Type	Article

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