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

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.

[1]  Monika Henzinger,et al.  Analysis of a very large web search engine query log , 1999, SIGF.

[2]  Dan Morris,et al.  Investigating the querying and browsing behavior of advanced search engine users , 2007, SIGIR.

[3]  Amanda Spink,et al.  Defining a session on Web search engines , 2007, J. Assoc. Inf. Sci. Technol..

[4]  Amanda Spink,et al.  Model for organizational knowledge creation and strategic use of information: Research Articles , 2005 .

[5]  Amanda Spink,et al.  A temporal comparison of AltaVista Web searching , 2005, J. Assoc. Inf. Sci. Technol..

[6]  Christoph Hölscher,et al.  Web search behavior of Internet experts and newbies , 2000, Comput. Networks.

[7]  Wai-Tat Fu,et al.  Exploratory information search by domain experts and novices , 2010, IUI '10.

[8]  Ian Ruthven,et al.  Searcher's Assessments of Task Complexity for Web Searching , 2004, ECIR.

[9]  Najafi Azadeh,et al.  REAL LIFE, REAL USERS AND REAL NEEDS: A STUDY AND ANALYSIS OF USER QUERIES ON THE WEB , 2008 .

[10]  Kristina Höök,et al.  Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 2012 .

[11]  Amanda Spink,et al.  Defining a session on Web search engines: Research Articles , 2007 .

[12]  Andrei Broder,et al.  A taxonomy of web search , 2002, SIGF.

[13]  Ido Guy,et al.  Best faces forward: a large-scale study of people search in the enterprise , 2012, CHI.

[14]  Ravi Kumar,et al.  Search in the Lost Sense of "Query": Question Formulation in Web Search Queries and its Temporal Changes , 2011, ACL.

[15]  Amanda Spink,et al.  An Analysis of Web Documents Retrieved and Viewed , 2003, International Conference on Internet Computing.

[16]  Anne Aula,et al.  How does search behavior change as search becomes more difficult? , 2010, CHI.

[17]  Anne Aula,et al.  Query Formulation in Web Information Search , 2003, ICWI.

[18]  Olivia R. Liu Sheng,et al.  Analysis of the query logs of a Web site search engine , 2005, J. Assoc. Inf. Sci. Technol..

[19]  Amanda Spink,et al.  Real life, real users, and real needs: a study and analysis of user queries on the web , 2000, Inf. Process. Manag..

[20]  Ryen W. White,et al.  WWW 2007 / Track: Browsers and User Interfaces Session: Personalization Investigating Behavioral Variability in Web Search , 2022 .

[21]  Amanda Spink,et al.  An analysis of Web searching by European AlltheWeb.com users , 2005, Inf. Process. Manag..

[22]  SpinkAmanda,et al.  An analysis of web searching by European AlltheWeb.com users , 2005 .

[23]  Amanda Spink,et al.  U.S. versus European web searching trends , 2002, SIGF.

[24]  Ophir Frieder,et al.  Temporal analysis of a very large topically categorized Web query log , 2007, J. Assoc. Inf. Sci. Technol..