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A predictive analysis of user navigation in the Internet is presented that exploits time-of-the-week data. Specifically, we investigate time as an environmental factor in making predictions about user navigation. An analysis is carried out of a large sample of user, navigation data (over 3.7 million sessions from 0.5 million users) in a mobile-Internet context to determine whether user surfing patterns vary depending on the time of the week on which they occur. We find that the use of timedoi:10.1145/1062745.1062817 dblp:conf/www/HalveyKS05 fatcat:d362xoktivgmxpnrku55nanjv4