ABSTRACT
We present preliminary results of a large-scale smartphone user study that examines how users interact with and consume energy on their personal mobile devices. Our dataset consists of over one millennium of user interaction traces from over 17300 BlackBerry users. Despite the scale and detail of the dataset, there are many research questions that it cannot answer; further user studies are therefore needed. We detail our insight into the major challenges in conducting a large-scale user study on BlackBerry devices.
- A. Agarwal, F. Deepinder, R. K. Sharma, G. Ranga, and J. Li. Effect of cell phone usage on semen analysis in men attending infertility clinic: an observational study. Fertility and sterility, 89(1):124--128, 2008.Google ScholarCross Ref
- BlackBerry Desktop Manager. Last visited: 29/09/2009. http://na.blackberry.com/eng/services/desktop/.Google Scholar
- BlackBerry Spyware Wasn't Ready for Prime Time. Last visited: 29/09/2009. http://www.wired.com/threatlevel/2009/07/blackberry-spyware/.Google Scholar
- Hossein Falaki, Ratul Mahajan, Srikanth Kandula, Dimitrios Lymberopoulos, Ramesh Govindan, and Deborah Estrin. Diversity in smartphone usage. In MobiSys '10: Proceedings of the 8th international conference on Mobile systems, applications and services, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- N. Kakabadse, G. Porter, and D. Vance. Addicted to technology. Business Strategy Review, 18(4):81, 2007.Google ScholarCross Ref
- N. K. Kakabadse, G. Porter, and D. Vance. The unbalanced high-tech life: are employers liable? Strategic Change, 18(1--2):1--13, 2009.Google Scholar
- Earl Oliver. A survey of platforms for mobile networks research. SIGMOBILE Mobile Computing and Communications Review, 12(4):56--63, 2008. Google ScholarDigital Library
- Earl Oliver and Hossein Falaki. Performance evaluation and analysis of delay tolerant networking. In MobiEval '07: Proceedings of the 1st international workshop on System evaluation for mobile platforms, pages 1--6, New York, NY, USA, 2007. ACM. Google ScholarDigital Library
- Earl Oliver and Srinivasan Keshav. Data driven smartphone energy level prediction. Technical Report CS-2010-06, University of Waterloo, April 2010.Google Scholar
- Ahmad Rahmati, Angela Qian, and Lin Zhong. Understanding human-battery interaction on mobile phones. In MobileHCI '07: Proceedings of the 9th international conference on Human computer interaction with mobile devices and services, pages 265--272, New York, NY, USA, 2007. ACM. Google ScholarDigital Library
- Research in Motion. Last visited: 29/09/2009. http://www.rim.com.Google Scholar
- C. Rosen. Our cell phones, ourselves. The New Atlantis, 6:26--45, 2004.Google Scholar
- A. Sleep. Technical Note Automatic Sleep/Wake Identification From Wrist Activity. Sleep, 15(5):461--469, 1992.Google ScholarCross Ref
Index Terms
- The challenges in large-scale smartphone user studies
Recommendations
Towards a Smartphone User Competency Evolution Model
SAICSIT '15: Proceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information TechnologistsOver the past few years smartphones have evolved from being basic devices that support stock-standard, static Operating Systems (OSs) to powerful devices that are capable of running dynamic, customizable OSs. In turn, these OSs also support the ...
Measuring user confidence in smartphone security and privacy
SOUPS '12: Proceedings of the Eighth Symposium on Usable Privacy and SecurityIn order to direct and build an effective, secure mobile ecosystem, we must first understand user attitudes toward security and privacy for smartphones and how they may differ from attitudes toward more traditional computing systems. What are users' ...
Comments