User session identification based on strong regularities in inter-Activity time

Aaron L Halfaker, Oliver Keyes, Daniel Kluver, Jacob Thebault-Spieker, Tien Nguyen, Kenneth Shores, Anuradha Uduwage, Morten Warncke-Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

53 Scopus citations

Abstract

Session identification is a common strategy used to develop metrics for web analytics and perform behavioral analyses of user-facing systems. Past work has argued that session identification strategies based on an inactivity threshold is inherently arbitrary or has advocated that thresholds be set at about 30 minutes. In this work, we demonstrate a strong regularity in the temporal rhythms of user initi-ated events across several different domains of online activ-ity (incl. video gaming, search, page views and volunteer contributions). We describe a methodology for identifying clusters of user activity and argue that the regularity with which these activity clusters appear implies a good rule-of-thumb inactivity threshold of about 1 hour. We conclude with implications that these temporal rhythms may have for system design based on our observations and theories of goal-directed human activity.

Original languageEnglish (US)
Title of host publicationWWW 2015 - Proceedings of the 24th International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages410-418
Number of pages9
ISBN (Electronic)9781450334693
DOIs
StatePublished - May 18 2015
Event24th International Conference on World Wide Web, WWW 2015 - Florence, Italy
Duration: May 18 2015May 22 2015

Publication series

NameWWW 2015 - Proceedings of the 24th International Conference on World Wide Web

Other

Other24th International Conference on World Wide Web, WWW 2015
Country/TerritoryItaly
CityFlorence
Period5/18/155/22/15

Keywords

  • Activity
  • Analytics
  • Human behavior
  • Metrics
  • Modeling
  • Regularities
  • User session

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