The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Identifying diverse usage behaviors of smartphone apps
Abstract
Smartphone users are increasingly shifting to using apps as "gateways" to Internet services rather than traditional web browsers. App marketplaces for iOS, Android, and Windows Phone platforms have made it attractive for developers to deploy apps and easy for users to discover and start using many network-enabled apps quickly. For example, it was recently reported that the iOS AppStore has more than 350K apps and more than 10 billion downloads. Furthermore, the appearance of tablets and mobile devices with other form factors, which also use these marketplaces, has increased the diversity in apps and their user population. Despite the increasing importance of apps as gateways to network services, we have a much sparser understanding of how, where, and when they are used compared to traditional web services, particularly at scale. This paper takes a first step in addressing this knowledge gap by presenting results on app usage at a national level using anonymized network measurements from a tier-1 cellular carrier in the U.S. We identify traffic from distinct marketplace apps based on HTTP signatures and present aggregate results on their spatial and temporal prevalence, locality, and correlation.
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Cites
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Self-citationFalaki, H., Mahajan, R., Kandula, S., Lymberopoulos, D., Govindan, R., & Estrin, D. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814453 · Cited by 838
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A first look at traffic on smartphones
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Self-citationProfiling resource usage for mobile applications: a cross-layer approach
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Cited by
Dehling, T., Gao, F., Schneider, S., & Sunyaev, A. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.3672 · Cited by 243
What Makes Smartphone Use Meaningful or Meaningless?
Lukoff, K., Yu, C., Kientz, J., & Hiniker, A. (2018) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3191754 · Cited by 205
Apps and eating disorders: A systematic clinical appraisal
Fairburn, C. G., & Rothwell, E. R. (2015) · International Journal of Eating Disorders · doi:10.1002/eat.22398 · Cited by 121
A machine learning based robust prediction model for real-life mobile phone data
Sarker, I. H. (2019) · Internet of Things · doi:10.1016/j.iot.2019.01.007 · Cited by 113
The hidden image of mobile apps: geographic, demographic, and cultural factors in mobile usage
Peltonen, E., Lagerspetz, E., Hamberg, J., Mehrotra, A., Musolesi, M., Nurmi, P., & Tarkoma, S. (2018) · Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services · doi:10.1145/3229434.3229474 · Cited by 56
Metadata
- Authors
- Xu, Q., Erman, J., Gerber, A., Mao, Z., Pang, J., & Venkataraman, S.
- Venue
- Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
- Publisher
- ACM
- Published
- 2011-11-02
- Pages
- 329-344
- OpenAlex
- W2067481044
- Cited by
- 414
- References
- 18
- FWCI
- 24.62
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Xu, Q., Erman, J., Gerber, A., Mao, Z., Pang, J., & Venkataraman, S. (2011). Identifying diverse usage behaviors of smartphone apps. Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference. https://doi.org/10.1145/2068816.2068847
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