Title :
LoyalTracker: Visualizing Loyalty Dynamics in Search Engines
Author :
Conglei Shi ; Yingcai Wu ; Shixia Liu ; Hong Zhou ; Huamin Qu
Author_Institution :
Hong Kong Univ. of Sci. & Technol., Hong Kong, China
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.
Keywords :
data analysis; data visualisation; human factors; search engines; text analysis; LoyalTracker; defection behavior; density map; flow metaphor; flow view; interactive visualization technique; loyalty dynamics visualization; search engine providers; switching behavior; user log data; user loyalty tracking; visual analytics system; word cloud; Behavioral science; Data visualization; Information analysis; Search engines; Search methods; Visual analytics; Time-series visualization; log data visualization; stacked graphs; text visualization;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2014.2346912