One of the most important dimensions of Web user information seeking behavior and search engine research is content-based behavior, and limited research has focused on content-based behavior of search engine users. The purpose of this study is to perform automatic new topic identification in search engine transaction logs using Monte-Carlo simulation. Sample data logs from FAST and Excite are used in the study. Findings show that Monte-Carlo simulation for new topic identification yields satisfactory results in terms of identifying topic continuations; however, the performance measures regarding topic shifts should be improved. (C) 2008 Elsevier B.V. All rights reserved.