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Privacy as part of the app decision-making process
Abstract
Smartphones have unprecedented access to sensitive personal information. While users report having privacy concerns, they may not actively consider privacy while downloading apps from smartphone application marketplaces. Currently, Android users have only the Android permissions display, which appears after they have selected an app to download, to help them understand how applications access their information. We investigate how permissions and privacy could play a more active role in app-selection decisions. We designed a short "Privacy Facts' display, which we tested in a 20-participant lab study and a 366-participant online experiment. We found that by bringing privacy information to the user when they were making the decision and by presenting it in a clearer fashion, we could assist users in choosing applications that request fewer permissions.
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“This is in line with the findings of Kelley et al. (2013) who found in their study on app decision-making process that users consider factors such as cost, functionality, design, ratings, reviews and downloads as more important than requested permissions.”
From Putting the privacy paradox to the test: Online privacy and security behaviors among users with technical knowledge, privacy awareness, and financial resources (2019) · cites this paper as Kelley et al. (2013)
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Gerber, N., Gerber, P., Drews, H., Kirchner, E., Schlegel, N., Schmidt, T., & Scholz, L. (2018) · Workshop on Socio-Technical Aspects in Security and Trust (STAST) · doi:10.1145/3167996.3167999 · Cited by 28
Understanding the Impact of Information Representation on Willingness to Share Information
Schneegaß, S., Poguntke, R., & Machulla, T. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300753 · Cited by 24
Personality segmentation of users through mining their mobile usage patterns
Razavi, R. (2020) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2020.102470 · Cited by 24
Using Statistical Information to Communicate Android Permission Risks to Users
Kraus, L., Wechsung, I., & Möller, S. (2014) · Workshop on Socio-Technical Aspects in Security and Trust (STAST) · doi:10.1109/stast.2014.15 · Cited by 25
Does Context in Privacy Communication Really Matter? — A Survey on Consumer Concerns and Preferences
Ebert, N., Ackermann, K. A., & Heinrich, P. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376575 · Cited by 25
Akter, M., Alghamdi, L., Kropczynski, J., Lipford, H. R., & Wisniewski, P. J. (2023) · Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544549.3585904 · Cited by 23
ATLAS: Automatically Detecting Discrepancies Between Privacy Policies and Privacy Labels
Jain, A., Rodríguez, D., Álamo, J. M. D., & Sadeh, N. (2023) · IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) · doi:10.1109/eurospw59978.2023.00016 · Cited by 26
Self-citationBreaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?
Ravichander, A., Black, A. W., Norton, T. B., Wilson, S., & Sadeh, N. (2021) · doi:10.18653/v1/2021.acl-long.319 · Cited by 27
Self-citationAbraham, M., McGill, M., & Khamis, M. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642668 · Cited by 28
Privacy policy analysis: A scoping review and research agenda
van der Schyff, K., Prior, S., & Renaud, K. (2024) · Computers & Security · doi:10.1016/j.cose.2024.104065 · Cited by 20
Understanding and Supporting Self-Tracking App Selection
Lee, J. H., Schroeder, J., & Epstein, D. A. (2021) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3494980 · Cited by 20
Shrestha, P. S., Mohamed, M., & Saxena, N. (2016) · ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) · doi:10.1145/2939918.2939924 · Cited by 19
Metadata
- Authors
- Kelley, P. G., Cranor, L. F., & Sadeh, N.
- Affiliations
- University of New Mexico (US)
- Carnegie Mellon University (US)
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2013-04-27
- Pages
- 3393-3402
- OpenAlex
- W2007784529
- Cited by
- 314
- References
- 17
- Citations by year
- 2026: 12 · 2025: 9 · 2024: 13 · 2023: 27 · 2022: 34 · 2021: 27 · 2020: 23 · 2019: 15 · 2018: 33 · 2017: 33 · 2016: 32 · 2015: 28 · 2014: 22 · 2013: 5
- FWCI
- 90.49
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- National Science Foundation
- Carnegie Mellon University
- Army Research Office
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- application permissions, privacy, user decision-making, personal information disclosure
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