I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Unveiling facebook: a measurement study of social network based applications
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Learning computer science concepts using iPhone applications
Journal of Computing Sciences in Colleges
A Social-Feedback Enriched Interface for Software Download
Journal of Organizational and End User Computing
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Online distributed applications are becoming more and more important for users nowadays. There are an increasing number of individuals and companies developing applications and selling them online. In the past couple of years, Apple Inc. has successfully built an online application distribution platform -- iTunes App Store, which is facilitated by their fashionable hardware such like iPad or iPhone. Unlike other traditional selling networks, iTunes has some unique features to advertise their application, for example, daily application ranking, application recommendation, free trial application usage, application update, and user comments. All of these make us wonder what makes an application popular in the iTunes store and why users are interested in some specific type of applications. We plan to answer these questions by using machine learning techniques.