Paper Info
Title
ERICA: Interaction Mining Mobile Apps.
Abstract
Design plays an important role in adoption of apps. App design, however, is a complex process with multiple design activities. To enable data-driven app design applications, we present interaction mining -- capturing both static (UI layouts, visual details) and dynamic (user flows, motion details) components of an app's design. We present ERICA, a system that takes a scalable, human-computer approach to interaction mining existing Android apps without the need to modify them in any way. As users interact with apps through ERICA, it detects UI changes, seamlessly records multiple data-streams in the background, and unifies them into a user interaction trace. Using ERICA we collected interaction traces from over a thousand popular Android apps. Leveraging this trace data, we built machine learning classifiers to detect elements and layouts indicative of 23 common user flows. User flows are an important component of UX design and consists of a sequence of UI states that represent semantically meaningful tasks such as searching or composing. With these classifiers, we identified and indexed more than 3000 flow examples, and released the largest online search engine of user flows in Android apps.
Year
DOI
Venue
2016
10.1145/2984511.2984581
UIST
Keywords
Field
DocType
Interaction mining, app design, design mining, user flows
World Wide Web,User experience design,Android (operating system),Computer science,Human–computer interaction,Mobile apps,Design activities,Online search,Scalability
Conference
Citations 
PageRank 
References 
19
0.72
13
Authors
3
Name
Order
Citations
PageRank
Biplab Deka1875.42
Zifeng Huang2592.86
Ranjitha Kumar331319.54