Mobile big-data-driven rating framework: Measuring the relationship between human mobility and app usage behavior

Yuanyuan Qiao, Xiaoxing Zhao, Jie Yang, Jiajia Liu

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Smart devices bring us ubiquitous mobile access to the Internet, making it possible to surf the Internet in mobile environments. With the pervasiveness of mobile Internet, much evidence shows that human mobility has heavy impact on app usage behavior. However, the relationship between them has not been quantified in any form. In this article, a rating framework is presented to demonstrate the existence of their connection. The core idea of a rating framework selects the most significant mobility features that may influence app usage behavior. In particular, we focus on three aspects of human mobility in urban areas: individual mobility characteristics, location, and travel behavior, from both the crowd and individual points of view. At last, by using a limited number of selected mobility and time features, high forecast accuracy is achieved in terms of app usage behavior of crowds and individuals, which verifies the effectiveness of the rating framework.

Original languageEnglish
Article number7474339
Pages (from-to)14-21
Number of pages8
JournalIEEE Network
Volume30
Issue number3
DOIs
StatePublished - 1 May 2016
Externally publishedYes

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