Unsupervised clickstream clustering for user behavior analysis

Gang Wang, Xinyi Zhang, Shiliang Tang, Haitao Zheng, Ben Y. Zhao

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

Abstract

Online services are increasingly dependent on user participation. Whether it's online social networks or crowdsourcing services, understanding user behavior is important yet challenging. In this paper, we build an unsupervised system to capture dominating user behaviors from clickstream data (traces of users' click events), and visualize the detected behaviors in an intuitive manner. Our system identifies "clusters" of similar users by partitioning a similarity graph (nodes are users; edges are weighted by clickstream similarity). The partitioning process leverages iterative feature pruning to capture the natural hierarchy within user clusters and produce intuitive features for visualizing and understanding captured user behaviors. For evaluation, we present case studies on two large-scale clickstream traces (142 million events) from real social networks. Our system effectively identifies previously unknown behaviors, e.g., dormant users, hostile chatters. Also, our user study shows people can easily interpret identified behaviors using our visualization tool.

Original languageEnglish (US)
Title of host publicationCHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery,
Pages225-236
Number of pages12
ISBN (Electronic)9781450333627
DOIs
StatePublished - May 7 2016
Externally publishedYes
Event34th Annual Conference on Human Factors in Computing Systems, CHI 2016 - San Jose, United States
Duration: May 7 2016May 12 2016

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other34th Annual Conference on Human Factors in Computing Systems, CHI 2016
Country/TerritoryUnited States
CitySan Jose
Period5/7/165/12/16

Keywords

  • Clickstream analysis
  • User behavioral model
  • Visualization

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

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