Article ID: | iaor201111779 |
Volume: | 52 |
Issue: | 2 |
Start Page Number: | 395 |
End Page Number: | 405 |
Publication Date: | Jan 2012 |
Journal: | Decision Support Systems |
Authors: | Wang Jingguo, Rao H Raghav, Xiao Nan |
Keywords: | risk, health services, statistics: regression, statistics: distributions |
The general public is increasingly using search engines to seek information on risks and threats. Based on a search log from a large search engine, spanning three months, this study explores user patterns of query submission and subsequent clicks in sessions, for two important risk related topics, healthcare and information security, and compares them to other randomly sampled sessions. We investigate two session‐level metrics reflecting users' interactivity with a search engine: session length and query click rate. Drawing from information foraging theory, we find that session length can be characterized well by the Inverse Gaussian distribution. Among three types of sessions on different topics (healthcare, information security, and other randomly sampled sessions), we find that healthcare sessions have the most queries and the highest query click rate, and information security sessions have the lowest query click rate. In addition, sessions initiated by the users with greater search engine activity level tend to have more queries and higher query click rates. Among three types of sessions, search engine activity level shows the strongest effect on query click rate for information security sessions and weakest for healthcare sessions. We discuss theoretical and practical implications of the study.