Falling asleep with Angry Birds, Facebook and Kindle: a large scale study on mobile application usage
Abstract
While applications for mobile devices have become extremely important in the last few years, little public information exists on mobile application usage behavior. We describe a large-scale deployment-based research study that logged detailed application usage information from over 4,100 users of Android-powered mobile devices. We present two types of results from analyzing this data: basic descriptive statistics and contextual descriptive statistics. In the case of the former, we find that the average session with an application lasts less than a minute, even though users spend almost an hour a day using their phones. Our contextual findings include those related to time of day and location. For instance, we show that news applications are most popular in the morning and games are at night, but communication applications dominate through most of the day. We also find that despite the variety of apps available, communication applications are almost always the first used upon a device's waking from sleep. In addition, we discuss the notion of a virtual application sensor, which we used to collect the data.
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One of the few articles published about mobile app usage examined data that was collected from 4125 users between August 2010 and January 2011.
“One of the few articles published about mobile app usage examined data that was collected from 4125 users between August 2010 and January 2011 [30].”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [30]
Communication apps were the most frequently used, 49.50% of app launches, whereas the proportion of health apps was only 0.26% of all app launches.
“Communication apps were the most frequently used, 49.50% of app launches, whereas the proportion of health apps was only 0.26% of all app launches [30].”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [30]
The study found that sessions with apps were short, averaging a little more than a minute.
“The study found that sessions with apps were short, averaging a little more than a minute, and that different types of apps were used during different times of the day.”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [30]
Different types of apps were used during different times of the day.
“The study found that sessions with apps were short, averaging a little more than a minute, and that different types of apps were used during different times of the day.”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [30]
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- Authors
- Böhmer, M., Hecht, B., Schöning, J., Krüger, A., & Bauer, G.
- Affiliations
- German Research Centre for Artificial Intelligence (DE)
- Northwestern University (US)
- FH Münster University of Applied Sciences (DE)
- Venue
- Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services
- Publisher
- ACM
- Published
- 2011-08-30
- Pages
- 47-56
- OpenAlex
- W2124555616
- Cited by
- 604
- References
- 15
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 15 · 2023: 16 · 2022: 22 · 2021: 39 · 2020: 51 · 2019: 44 · 2018: 49 · 2017: 56 · 2016: 77 · 2015: 78 · 2014: 63 · 2013: 51 · 2012: 23
- FWCI
- 33.15
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Mobile and Web Applications
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- Android, communication apps, news apps, mobile games
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