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We conducted a user study with 380 Android users, profiling them according to two key privacy behaviors: the number of apps installed, and the Dangerous permissions granted to those apps. We identified four unique privacy profiles: 1) Privacy Balancers (49.74% of participants), 2) Permission Limiters (28.68%), 3) App Limiters (14.74%), and 4) the Privacy Unconcerned (6.84%). App and Permission Limiters were significantly more concerned about perceived surveillance than Privacy Balancers and the Privacy Unconcerned. App Limiters had the lowest number of apps installed on their devices with the lowest intention of using apps and sharing information with them, compared to Permission Limiters who had the highest number of apps installed and reported higher intention to share information with apps. The four profiles reflect the differing privacy management strategies, perceptions, and intentions of Android users that go beyond the binary decision to share or withhold information via mobile apps.
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Still Creepy After All These Years:The Normalization of Affective Discomfort in App Use
It is not well understood why people continue to use privacy-invasive apps they consider creepy. We conducted a scenario-based study (n = 751) to investigate how the intention to use an app is influenced by affective perceptions and privacy concerns. We show that creepiness is one facet of affective discomfort, which is becoming normalized in app use. We found that affective discomfort can be negatively associated with the intention to use a privacy-invasive app. However, the influence is mitigated by other factors, including data literacy, views regarding app data practices, and ambiguity of the privacy threat. Our findings motivate a focus on affective discomfort when designing user experiences related to privacy-invasive data practices. Treating affective discomfort as a fundamental aspect of user experience requires scaling beyond the point where the thumb meets the screen and accounting for entrenched data practices and the sociotechnical landscape within which the practices are embedded.
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- Award ID(s):
- 2219354
- PAR ID:
- 10339561
- Date Published:
- Journal Name:
- CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
- Page Range / eLocation ID:
- 1 to 19
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3491102.3502112
