Visible to the public LoyalTracker: Visualizing Loyalty Dynamics in Search Engines

TitleLoyalTracker: Visualizing Loyalty Dynamics in Search Engines
Publication TypeJournal Article
Year of Publication2014
AuthorsConglei Shi, Yingcai Wu, Shixia Liu, Hong Zhou, Huamin Qu
JournalVisualization and Computer Graphics, IEEE Transactions on
Volume20
Pagination1733-1742
Date PublishedDec
ISSN1077-2626
KeywordsBehavioral science, Data analysis, data visualisation, Data visualization, defection behavior, density map, flow metaphor, flow view, human factors, Information analysis, interactive visualization technique, log data visualization, LoyalTracker, loyalty dynamics visualization, search engine providers, search engines, Search methods, stacked graphs, switching behavior, text analysis, text visualization, Time-series visualization, user log data, user loyalty tracking, visual analytics, visual analytics system, word cloud
Abstract

The huge amount of user log data collected by search engine providers creates new opportunities to understand user loyalty and defection behavior at an unprecedented scale. However, this also poses a great challenge to analyze the behavior and glean insights into the complex, large data. In this paper, we introduce LoyalTracker, a visual analytics system to track user loyalty and switching behavior towards multiple search engines from the vast amount of user log data. We propose a new interactive visualization technique (flow view) based on a flow metaphor, which conveys a proper visual summary of the dynamics of user loyalty of thousands of users over time. Two other visualization techniques, a density map and a word cloud, are integrated to enable analysts to gain further insights into the patterns identified by the flow view. Case studies and the interview with domain experts are conducted to demonstrate the usefulness of our technique in understanding user loyalty and switching behavior in search engines.

DOI10.1109/TVCG.2014.2346912
Citation Key6876038