Annual Meeting Contributed Papers 2009 START Conference Manager    

To What Degree Can Log Data Profile a Web Searcher?

Bernard Jansen, Danille Booth, Daehee Park, Mimi Zhang, Ying Zhang, Ashish Kathuria and Pat Bonner

(Submission #40)


In this paper, we report ongoing efforts in a large scale research project to develop methods for profiling individual Web search engine users by leveraging data recorded in the transaction logs of search engines. Our research aim is to investigate how completely one can profile a Web searcher using log data. Taking a broad brush approach, we present an array of profiling attributes to illustrate the spectrum of user characteristics possible from log data. Specifically, we present ongoing research for determining a userís location, geographical interest, topic of interest, level of interest, the degree of commercial intent, whether or not the user is planning on making a purchase, and if the user is going to click a link. We present the state of our ongoing research in user profiling along with that of other researchers. Our findings show that one can develop a fairly robust profile of a Web searcher using log data. We also discuss issues of determining the specific identity of the user. We conclude with a discussion of the implications for the areas of system development, online advertising, privacy, and policies concerning the use of such profiling.

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